To see the other types of publications on this topic, follow the link: Biometric identification.
Journal articles on the topic 'Biometric identification'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Biometric identification.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Shopon, Md, Sanjida Nasreen Tumpa, Yajurv Bhatia, K. N. Pavan Kumar, and Marina L. Gavrilova. "Biometric Systems De-Identification: Current Advancements and Future Directions." Journal of Cybersecurity and Privacy 1, no. 3 (August 31, 2021): 470–95. http://dx.doi.org/10.3390/jcp1030024.
Full textAbstract:
Biometric de-identification is an emerging topic of research within the information security domain that integrates privacy considerations with biometric system development. A comprehensive overview of research in the context of authentication applications spanning physiological, behavioral, and social-behavioral biometric systems and their privacy considerations is discussed. Three categories of biometric de-identification are introduced, namely complete de-identification, auxiliary biometric preserving de-identification, and traditional biometric preserving de-identification. An overview of biometric de-identification in emerging domains such as sensor-based biometrics, social behavioral biometrics, psychological user profile identification, and aesthetic-based biometrics is presented. The article concludes with open questions and provides a rich avenue for subsequent explorations of biometric de-identification in the context of information privacy.
2
Mudhafer Taher Al Mossawy, Mais, and Loay E. George. "A digital signature system based on hand geometry - Survey." Wasit Journal of Computer and Mathematics Science 1, no. 1 (April 1, 2022): 1–14. http://dx.doi.org/10.31185/wjcm.vol1.iss1.18.
Full textAbstract:
In recent years large number of emerging automated applications faces the need to have recognition abilities of persons using their own self biometrics, before they can access the applications services. Nowadays, Biometric recognition is used, it can be used as automatic identification or automatic verification of persons based on their physiological or behavioral characteristics. There are no perfect biometric measurements;each biometry has its advantages and limitations. Each biometry requires specific vital identity to answer the identification or verification question. The suitability of a particular biometry for a particular application depends on many factors. Hand geometry/shape is a very simple biometric technology that uses the measurements of human hand to verify the identity of the individuals. The measurements include the distance between certain mark points, shape and width of fingers and size of palm. The biometric systems that employing hand geometry become widely used since they have high public acceptance. This article aims to survey several articles found in literature about hand based biometric system, and to compare different methods of biometric recognition that based on hand geometry.
3
., Himanshi, Trisha Gulati, and Yasha Hasija. "Biometrics in Healthcare." INTERNATIONAL JOURNAL OF ADVANCED PRODUCTION AND INDUSTRIAL ENGINEERING 3, no. 2 (April 15, 2018): 13–17. http://dx.doi.org/10.35121/ijapie201804223.
Full textAbstract:
Biometrics is the discipline to measure physical human characteristics for the identification and authentication of an individual. Since ancient times, people have used voice, face, and other characteristics for the identification of an individual. With evolution, we take the individual characteristics like fingerprint scans, retina and iris images, etc., as inputs to the computer systems and then store or verify them with existing records. This report discusses biometrics and its recent roles found in the field of healthcare, medicine, genetics, and biotechnology. It includes the concept of biometrics, the system used for biometric recognition and its working, types of biometric systems, the different system algorithms applied, and system modules which are well illustrated with flow charts and block diagrams. Some of the health institutes in developed countries have started using biometric systems for checking patients and/or doctors. Biometry has enabled the proper organization and storage of the health records of individuals in medical institutes. Biometric authentication is also finding a distinct role in foiling medical claims fraud highlighting the advantages it. Even after processing via a very accurate biometric system, there is a chance of a false result due to some disease or injury to the body part subjected to biometry or faulty system leading to some error. There is also a possibility that the biometric system may harm our bodies. Moreover, biometric records need really tight system security to prevent any kind of misuse. Biometrics has a great potential to find a lot more uses in the field of healthcare. Many ideas are being proposed for implementation. In the future, biometrics can be used to detect potential disease and risks by using methods like adiposity measurement and Gas Discharge Visualization (GDV).
4
Ayanaba, Rasheed Abubakar. "Image-assisted Biometric Identification." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (July 24, 2022): 131–38. http://dx.doi.org/10.22624/aims/crp-bk3-p22.
Full textAbstract:
Biometrics is a rapidly developing technology that has seen widespread use in forensics applications such as criminal identification, secure access, and prison security. A biometric system is a pattern recognition system that recognizes a person by determining the authenticity of a physiological and/or behavioural feature that that person possesses. One of the most widely accepted biometrics utilized by humans in their visual interactions is image- assisted based (facial) biometric. Image-assisted biometric identification is the use of face recognition technology in capturing image of a unique feature of an individual such as an eye or face, and comparing it with a template captured earlier and stored a database. Face recognition is one of the more recent biometrics technologies. The system examines face features and tries to match them to a database of digitized images. This technology is quite new, having only been available commercially since the 1990s. Face recognition has gotten a lot of press after the 9/11 attacks because of its capacity to identify known terrorists and criminals. [1]. Although the technology is mostly utilized for security and law enforcement, there is growing interest in other applications. Keyword: Image-assisted based biometric identification, Face recognition technology, Image
5
Diac, Madalina Maria, Simona Irina Damian, Bianca Diana Butincu, Anton Knieling, and Diana Bulgaru Iliescu. "Ethical Aspects of Biometric Identification." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 14, no. 4 (December 19, 2023): 124–39. http://dx.doi.org/10.18662/brain/14.4/496.
Full textAbstract:
The term biometrics derives from Greek (bio=life and metrics=measure) and implies the measurement of biological signs. Biometrics is the science of recognizing people based on their physical, behavioral, and physiological attributes, such as fingerprint, face scan, iris, retina, and voice. The present paper aims to develop a study on biometric identification. The major objective of the study is to conduct a survey among the Romanian population on the importance and knowledge of biometric identification methods. This objective was achieved by assessing the knowledge held by the general population of Romania regarding biometric indicators and the degree of adaptability and openness of citizens related to the widest possible implementation of biometrics. The study was based on conducting a quantitative analysis using a questionnaire. Due to the high degree of accessibility, the online environment was chosen as a method of application, distribution being made through social networks. A biometric template digitizes the human body, it has been argued that the collection of biometric identifiers not only interferes with the privacy and right to protection of a person's data, but also with the integrity of an individual's body. In conclusion, the creation and storage of a unique biometric template must be seen in relation to the purpose of the operation. The protection of citizens from criminal activities is a primary obligation of the state. However, it must be exercised with due respect for a number of fundamental ethical values and in the light of modern human rights law.
6
Aruna, Boda, and Dr M. Kezia Joseph. "Multimodal Biometrics for Human Identification usingArtificial Intelligence." International Journal of Emerging Science and Engineering 12, no. 1 (December 30, 2023): 1–6. http://dx.doi.org/10.35940/ijese.a4278.1212123.
Full textAbstract:
Multimodal biometric systems combine multiple biometric modalities to enhance the accuracy and security of human identification. Instead of relying on a single biometric trait (such as fingerprint or face), these systems use a combination of different biometric characteristics to provide a more robust and reliable identification process. The key idea behind multimodal biometrics is that the fusion of diverse biometric data can overcome the limitations of individual modalities, resulting in higher accuracy and lower error rates.
7
Reddy, M. V. Bramhananda, and V. Goutham. "IRIS TECHNOLOGY: A REVIEW ON IRIS BASED BIOMETRIC SYSTEMS FOR UNIQUE HUMAN IDENTIFICATION." International Journal of Research -GRANTHAALAYAH 6, no. 1 (January 31, 2018): 80–90. http://dx.doi.org/10.29121/granthaalayah.v6.i1.2018.1596.
Full textAbstract:
Biometric features are widely used in real time applications for unique human identification. Iris is one of the physiological biometric features which are regarded as highly reliable in biometric identification systems. Often iris is combined with other biometric features for robust biometric systems. It is also observed that biometrics is combined with cryptography for stronger security mechanisms. Since iris is unique for all individuals across the globe, many researchers focused on using iris or along with other biometrics for security with great precision. Multimodal biometric systems came into existence for better accuracy in human authentication. However, iris is considered to be most discriminatory of facial biometrics. Study of iris based human identification in ideal and non-cooperative environments can provide great insights which can help researchers and organizations that depend on iris-based biometric systems. The technical knowhow of iris strengths and weaknesses can be great advantage. This is more important in the wake of widespread use of smart devices which are vulnerable to attacks. This paper throws light into various iris-based biometric systems, issues with iris in the context of texture comparison, cancellable biometrics, iris in multi-model biometric systems, iris localization issues, challenging scenarios pertaining to accurate iris recognition and so on.
8
Chinyemba, Melissa K., and Jackson Phiri. "Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions." Zambia ICT Journal 2, no. 1 (June 29, 2018): 35–43. http://dx.doi.org/10.33260/zictjournal.v2i1.49.
Full textAbstract:
The current physical and cybersecurity systems rely on traditional three-factor authentication to mitigate the threats posed by insider attacks. Key is the use of biometric information. Biometrics are a unique measurement and analysis of the unique physiological special traits such as voice, eye structure and others that can be used in the discipline of varying person identification. Biometry, which is the analysis of these biometrics is a complex process but guarantees identification and non-repudiation. If used to identify humans then several issues such as where is the biometric data stored? Who has access to it? And how does one ensure that such data satisfies the principle of availability. To achieve availability, secure transportation arises. To achieve transportation, non-repudiation, confidentiality and authentication, integrity arise. A storage and transport system is recommended to these challenges. In this paper, we explore the gaps into how public and private institution store and manage biometrics information. We benchmarked each organization again the ISO 30107 and ISO 24745. Our results show that while most companies are adopting and using biometrics systems, few have adopted the ISO biometrics standards that govern the storage and management of biometric information and hence creating security risk.
9
Yaacob, Mohd Noorulfakhri, Syed Zulkarnain Syed Idrus, Wan Azani Wan Mustafa, Mohd Aminudin Jamlos, and Mohd Helmy Abd Wahab. "Identification of the Exclusivity of Individual’s Typing Style Using Soft Biometric Elements." Annals of Emerging Technologies in Computing 5, no. 5 (March 20, 2021): 10–26. http://dx.doi.org/10.33166/aetic.2021.05.002.
Full textAbstract:
Biometric is used as a main security fence in a computer system. The unique characteristics of a person can be distinguished from each other. Human’s biometrics can be categorized into three types: morphological, biological and behavioural. Morphological biometrics uses physical features for recognition. Biological biometrics used to identify user based on biological features. Behavioural biometrics such as gender, culture, height and weight can be used as an additional security measure within a system. These biometric behavioural features are also known as soft biometric. This study uses soft biometric elements (gender, culture, region of birth and educational level) in the keystroke dynamic study to distinguish typing patterns in each of these categories. The Support Vector Machine (SVM) classification method is used to perform this classification for soft biometric identification. The results of this study have shown that soft biometrics in keystroke dynamic can be used to distinguish group of individuals typing.
10
Yin, Jing Hai, Zheng Dong Mu, and Jian Feng Hu. "Design of Identification System Based on BCI." Applied Mechanics and Materials 496-500 (January 2014): 1975–78. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1975.
Full textAbstract:
Nowadays EEG-based identification biometric research becomes a new topic. Due to the current biometric technology are still exist some problems, therefore, an urgent needed is to find a new biometric technology. In this paper, we use EEG signals as biometrics, which is home to a new biometric research trends, cutting-edge and exploratory nature, there is a good prospect. We establish a set of EEG-based identification systems and medium-sized EEG signatures, explore effective methods of analysis biometric technology to make up for past deficiencies, to further improve and develop the theory of biometric technologies and applications for EEG-based identification technology promotion foundation.
11
Kuznetsov, Denis. "Identification of a Personality." MATEC Web of Conferences 155 (2018): 01018. http://dx.doi.org/10.1051/matecconf/201815501018.
Full textAbstract:
Biometric technologies are based on biometrics, measurement of the unique characteristics of a certain person. These are the unique signs received by a person from birth and acquired characteristics that can change under the influence of time or external environment. This article discusses the principles of operation, types of biometric identification systems, describes examples and areas of their application.
12
Kulikov, A. A. "Application of biometric systems in face identification technologies." Russian Technological Journal 9, no. 3 (June 28, 2021): 7–14. http://dx.doi.org/10.32362/2500-316x-2021-9-3-7-14.
Full textAbstract:
The paper presents an analytical review of the application of biometric recognition systems in relation to facial image identification technologies. The classification of biometric systems is presented. The trends of technological progress in the field of biometrics and facial recognition capabilities are considered. It is determined that in 2020 there is a trend of transition from the use of biometric recognition technologies in traditional state security systems to the sphere of commercial and user applications. The process of «linking» encryption keys and passwords with the biometric parameters of the data subject is described. It is proposed that a biometric feature and a biometrics parameter mean a certain value that has a physical meaning that characterizes the subject itself. The possibility of using circular neighborhood and bilinear interpolation of pixel intensity values in biometrics is also presented. This will make it possible to build a local binary template. In order to solve the problem of identification of persons, it is advisable to investigate the essence of biometric systems in the technologies of identification of persons, their types, identifying the shortcomings of each of them, on the basis of which to present the directions of elimination and search for the most reliable technologies. The essence of the use of biometric systems in the technologies of identification of persons is, for example, that the user can provide the bank or other counterparty with evidence that it is he who wants to use the services on his accounts. At the same time, the demand has increased for contactless biometric solutions. These technologies are implemented in order to conduct additional biometric verification of users. This allows to minimize possible fraud or violation of the internal rules of the service, for example, the transfer of accounts of some registered users to others.
13
Rajvanshi, Saumya, Shiv Chauhan, and Savneet Kaur. "A New Wave in Biometric System: Systematic Study." CGC International Journal of Contemporary Technology and Research 4, no. 2 (August 5, 2022): 300–305. http://dx.doi.org/10.46860/cgcijctr.2022.07.31.300.
Full textAbstract:
Biometric system is a technique used to identify a person using its personal identification methods. The main concept of biometric systems is to provide confidentiality and security to the user. A number of biometric systems are introduced but some systems are widely used and are famous because of their usage and security they provide. Physiological and Behavioral biometrics are the two types of biometric systems. Biometric systems include physiological biometrics like face recognition, fingerprint recognition, iris recognition and behavioral biometrics like signature recognition and voice recognition. All these recognition systems are discussed in this research paper. Biometric systems work on three levels: Enrollment, Verification, and Identification. Enrollment is the process in which patterns are captured from the user and stored in the database. Verification means to confirm that the sample entered by the user belongs to him or not. When the user wants to access the data then the user must use his/her biometrics so that the system checks that the person who wants to access the data is the real owner of the data or not. This process is identification. All three levels are the working levels of the Biometric System. In earlier years, biometrics were used only at ground levels to provide basic security to data but now the tables have turned. It is playing a major role in providing security to our data. Biometrics are not only used in day-to-day life in phone unlocking, phone assistants, attendance systems but also used at advanced levels like in airports, border security, cloud computing etc. In this research paper, we will discuss the future scope of biometric systems and how it could even change the future.
14
Gupta, Ms Neha. "A New Wave in Biometric System: Systematic Study incorporated with Artificial Intelligence." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 10, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem33563.
Full textAbstract:
Biometric system is a technique used to identify a person using its personal identification methods. The main concept of biometric systems is to provide confidentiality and security to the user. A number of biometric systems are introduced but some systems are widely used and are famous because of their usage and security they provide. Physiological and Behavioral biometrics are the two types of biometric systems. Biometric systems include physiological biometric like face recognition, finger print recognition, ir is recognition and behavioral biometrics like signature recognition and voice recognition. All these recognition systems are discussed in this research paper. Biometric systems work on three levels: Enrollment, Verification, and Identification. Enrollment is the process in which patterns are captured from the user and stored in the database. Verification means to confirm that the sample entered by the user belongs to him or not. When the user wants to access the data then the user must use his/her biometrics that the systematic hacks that the person who wants to access the data is the real owner of the data or not. This process is identification. All three levels are the working levels of the Biometric System. In earlier years, biometrics was used only at ground levels to provide basic security to data but now the tables have turned. It is playing a major role in providing security to our data. Biometrics are not only used in day-to-day life in phone unlocking, phone assistants, attendance systems but also used at advanced levels like in airports, border security, cloud computing etc. In this research paper, we will discuss the future scope of biometric systems and how it could even change the future.
15
Hidayat, Taopik, Nurul Khasanah, Daniati Uki Eka Saputri, Umi Khultsum, and Risca Lusiana Pratiwi. "Klasifikasi Gambar Palmprint Berbasis Multi-Kelas Menggunakan Convolutional Neural Network." Jurnal Sistem Informasi 11, no. 1 (February 26, 2022): 01–06. http://dx.doi.org/10.51998/jsi.v11i1.474.
Full textAbstract:
Abstract—Biometric technology is developing to be the most relevant mechanism in identity identification. The main purpose of an identity management system is to be able to establish a relationship between individuals and their identities when needed under certain conditions. Among the newly proposed identity verification and personal identification technologies, biometrics is rapidly becoming the most relevant mechanism for identity recognition. This study proposes a new biometric recognition method for authentication and personal identification. Palm image recognition based on image processing for authentication and personal identification is proposed, namely competitive coding using the Convolutional Neural Network (CNN) and Local Binary Pattern (LBP) texture extraction with hyperparameter modifications. The dataset used comes from the Birjand University Mobile Palmprint Database (BMPD) which consists of 20 classes with a total of 800 palm images. The research was conducted using a data distribution of 80% training data and 20% validation data. The tests carried out resulted in a good accuracy value of the proposed model of 93.3% for the training process and 90.6% for the validation process. Keywords: Biomethric, CNN, LBP Intisari— Teknologi biometrik berkembang menjadi mekanisme paling relevan dalam pengidentifikasi identitas. Tujuan utama dari sistem manajemen identitas adalah untuk dapat membangun hubungan antara individu dan identitas mereka ketika dibutuhkan dalam kondisi tertentu. Di antara verifikasi identitas yang baru diusulkan dan teknologi identifikasi pribadi, biometrik dengan cepat menjadi mekanisme yang paling relevan untuk pengenalan identitas. Penelitian ini mengusulkan metode pengenalan biometrik terbaru untuk otentikasi dan identifikasi pribadi. Pengenalan citra telapak tangan berbasis image processing untuk otentikasi dan identifikasi pribadi yang diusulkan yaitu pengkodean kompetitif menggunakan metode Convolutional Neural Network (CNN) dan ekstraksi tekstur Local Binary Pattern (LBP) dengan modifikasi hyperparameter. Dataset yang digunakan berasal dari Birjand University Mobile Palmprint Database(BMPD) yang terdiri dari 20 kelas dengan total 800 citra telapak tangan. Penelitian dilakukan dengan menggunakan distribusi data sebesar 80% data training dan 20% data validasi. Pengujian yang dilakukan menghasilkan nilai akurasi yang baik dari model yang diusulkan sebesar 93,3% untuk proses training dan 90,6% untuk proses validasi. Kata Kunci: Biometrik, CNN, LBP
16
Lutsenko, K., and K. Nikulin. "VOICE SPEAKER IDENTIFICATION AS ONE OF THE CURRENT BIOMETRIC METHODS OF IDENTIFICATION OF A PERSON." Theory and Practice of Forensic Science and Criminalistics 19, no. 1 (April 2, 2020): 239–55. http://dx.doi.org/10.32353/khrife.1.2019.18.
Full textAbstract:
The article deals with the most widespread biometric identification systems of individuals, including voice recognition of the speaker on video and sound recordings. The urgency of the topic of identification of a person is due to the active informatization of modern society and the increase of flows of confidential information.
The branches of the use of biometric technologies and their general characteristics are given. Here is an overview of the use of identification groups that characterize the voice. Also in the article the division of voice identification systems into the corresponding classes is given.
The main advantages of voice biometrics such as simplicity of system realization are considered; low cost (the lowest among all biometric methods); No need for contact, the voice biometry allows for long-range verification, unlike other biometric technologies.
The analysis of existing methods of speech recognition recognition identifying a person by a combination of unique voice characteristics, determining their weak and strong points, on the basis of which the choice of the most appropriate method for solving the problem of text-independent recognition, Namely the model of Gaussian mixtures, was carried out.
The prerequisite for the development of speech technologies is a significant increase in computing capabilities, memory capacity with a significant reduction in the size of computer systems. It should also be Noted the development of mathematical methods that make it possible to perform the Necessary processing of an audio signal by isolating informative features from it.
It has been established that the development of information technologies, and the set of practical applications, which use voice recognition technologies, make this area relevant for further theoretical and practical research.
17
B.R., Rohini, and Thippeswamy G. "BIOMETRICS-A PRELIMINARY APPROACH." International Journal of Research -GRANTHAALAYAH 5, no. 4RACSIT (April 30, 2017): 47–52. http://dx.doi.org/10.29121/granthaalayah.v5.i4racsit.2017.3350.
Full textAbstract:
Authentication plays a vital role in Information security. The need for identification of legitimate user has increased in the waking concerns for global security. Biometric recognition Systems is a major tool for Authentication mechanism. Biometrics is the ability to identify and authenticate an individual using one or more of their behavioral or physical characteristics. The Study of Different Biometric Modalities gives a better understanding of Biometric Techniques. We focus our Study on Face Biometrics. This paper emphasizes on better understanding of introduction to Biometrics, Biometric Modalities and Face recognition Techniques.
18
Omar, Bayan, Hamsa D. Majeed, Siti Zaiton Mohd Hashim, and Muzhir Al-Ani. "New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System." UHD Journal of Science and Technology 6, no. 1 (February 11, 2022): 12–20. http://dx.doi.org/10.21928/uhdjst.v6n1y2022.pp12-20.
Full textAbstract:
This article delves into the power of multi-biometric fusion for individual identification. a new feature-level algorithm is proposed that is the Dis-Eigen algorithm. Here, a feature-fusion framework is proposed for attaining better accuracy when identifying individuals for multiple biometrics. The framework, therefore, underpins the new multi-biometric system as it guides multi-biometric fusion applications at the feature phase for identifying individuals. In this regard, the Face-fingerprints of 20 individuals represented by 160 images were used in this framework . Experimental resultants of the proposed approach show 93.70 % identification rate with feature-level fusion multi-biometric individual identification.
19
Kulanbay, Sh B., G. S. Beketova, and E. N. Tulegenova. "RESEARCH AND DEVELOPMENT OF BIOMETRIC METHODS." Herald of the Kazakh-British technical university 20, no. 2 (July 2, 2023): 115–24. http://dx.doi.org/10.55452/1998-6688-2023-20-2-115-124.
Full textAbstract:
Identification systems play a very important role in today's society. Complex security requirements have prompted experts to explore ways in which biometrics can be used to identify customers. In this article, the concept of biometrics, biometric data and its variants are considered. The purpose of the article is to study the process of identification, to produce its improved version and introduce innovation. Thus, the following points served as a research method:- Initialization.- Fitness functions.- Unclear clusterleu method.The results showed that the advancement of biometric systems and biometric sensors can improve the identity and prevent others from using the identity, the system has great potential to improve the security and accuracy of the biometric technology system. Biometric systems increase the security of users, as well as ensure accuracy in the identification of personal identity. Thus, the accuracy of the proposed method is compared with four modern methods. The comparison shows that the proposed approach provided a high accuracy of about 99.89% and a low error rate of 0.18%. It turns out that there is real potential for the integration of fingerprints and iris biometrics in many subjects with the appropriate assessment.
20
Medjahed, Chahreddine, Abdellatif Rahmoun, Christophe Charrier, and Freha Mezzoudj. "A deep learning-based multimodal biometric system using score fusion." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (March 1, 2022): 65. http://dx.doi.org/10.11591/ijai.v11.i1.pp65-80.
Full textAbstract:
Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work proposes efficent multimodal biometric systems based on matching score concatenation fusion of face, left and right palm prints. Multimodal biometric identification systems using convolutional neural networks (CNN) and k-nearest neighbors (KNN) are proposed and trained to recognize and identify individuals using multi-modal biometrics scores. Some popular biometrics benchmarks such as FEI face dataset and IITD palm print database are used as raw data to train the biometric systems to design a strong and secure verification/identification system. Experiments are performed on noisy datasets to evaluate the performance of the proposed model in extreme scenarios. Computer simulation results show that the CNN and KNN multi-modal biometric system outperforms most of the most popular up to date biometric verification techniques.
21
Migliorini, Sara. "Biometric Harm." Law, Technology and Humans 5, no. 2 (November 21, 2023): 238–51. http://dx.doi.org/10.5204/lthj.2830.
Full textAbstract:
This article argues in favour of the recognition of biometric harm, which is a specific type of harm arising from the use of biometrics to identify and classify people without a valid legal justification. The importance and pervasiveness of biometric technologies have increased. The development of biometric systems is rapidly advancing; however, their potential negative implications for individuals and society are routinely dismissed or willingly ignored. Biometrics deeply affects some of the basic needs of humans, including the need to step out of one’s social identities to enjoy unobserved time and the need to self-represent oneself in all social relationships. Such necessities are preserved by the legal system via high-ranked provisions that protect personhood, dignity, the right to private life and the right to express one’s personality. Because of these negative effects on core human necessities and legal values, this paper submits that biometric identification should be considered harmful, unless justified by another equally fundamental legal value. In line with other restrictions of the involved fundamental values, necessity and law enforcement purposes may justify biometric identification. Conversely, it is submitted that consent, while essential, does not fulfil the requirements of a stand-alone justification for biometric harm.
22
Shilpi Sharma, Swapnita Srivastava, Vipul Narayan, Rahul Sawhney,. "Ear Biometry: Protection Safeguarding Ear Acknowledgment Framework utilizing Transfer Learning in Industry 4.0." Journal of Electrical Systems 20, no. 3s (April 4, 2024): 1397–412. http://dx.doi.org/10.52783/jes.1517.
Full textAbstract:
Human-Recognition using biometric features proposes a noble way of uniquely identifying individuals considering they do not require people to keep loads of passwords in mind to prove their identity. Biometrics have aided in people unable to render other’s identity as well and have advanced over the years. Identification using ear biometric technique is considered to outrun other features since passive human involvement and ease-of-access are its strong set of attributes, not seen in any other biometric techniques. It has managed to identify criminals in the Crime Branch and has various helpful applications in the industry. Even in times of pandemic, it can serve its purpose in identifying individuals due to its feasibility. Models for Ear Image Identification have been proposed by various researchers over time utilizing Deep Learning and its Networks achieving high accuracy results, presenting faster and accurate identification models, boosting Ear Biometry as a secure Human Identification Tool. The learnings of this study on the AMI Ear Dataset and the OCEar dataset prove Ear Uniqueness of individuals demonstrating the identification of individuals, introducing passive identification into play, as well as computes on another dataset OCEar to study the similarity of both ears for identifying an individual.
23
Syryamkim, V. I., D. N. Kuznetsov, and A. S. Kuznetsova. "Biometric identification." IOP Conference Series: Materials Science and Engineering 363 (May 2018): 012005. http://dx.doi.org/10.1088/1757-899x/363/1/012005.
Full text
24
Richards, Donald R. "Biometric Identification." Information Systems Security 6, no. 2 (January 1997): 28–44. http://dx.doi.org/10.1080/10658989709342534.
Full text
25
Jain, Anil, Lin Hong, and Sharath Pankanti. "Biometric identification." Communications of the ACM 43, no. 2 (February 2000): 90–98. http://dx.doi.org/10.1145/328236.328110.
Full text
26
Jing Yang, Et al. "Multimedia Identification and Analysis Algorithm of Piano Performance Music Based on Deep Learning." Journal of Electrical Systems 19, no. 4 (January 25, 2024): 196–210. http://dx.doi.org/10.52783/jes.632.
Full textAbstract:
In the biometric biomedical applications, the study presents a pioneering research endeavor focused on the development of a multimedia identification and analysis algorithm tailored for piano performance music. With the power of deep learning techniques, this algorithm has been designed to address the intricate challenges posed by the convergence of musical data analysis and biometrics. The core objectives encompass the extraction, recognition, and interpretation of biometric information from piano performances, exploring the intricate patterns, nuances, and individualistic characteristics inherent to musicians. The study focuses on the development of advanced biometric authentication and identification systems capable of capturing and analyzing a user's unique behavioral patterns across diverse modalities. These biometric modalities offer the potential for highly secure and non-intrusive user identification. Hence, this paper developed an architecture of Marker Controlled Point (MCP) Estimation for the computation of the gesture in biometric-based applications. This architecture utilizes markers or reference points to precisely track and analyze user gestures, resulting in accurate and reliable biometric data. The research details the architecture's implementation, integrating advanced deep-learning techniques for feature extraction, pattern recognition, and authentication. This system finds versatile applications in various domains, from healthcare and cybersecurity to finance, where secure and user-friendly authentication is paramount. Experimental results underscore the system's effectiveness and robustness, demonstrating its potential for enhancing biometric authentication. The proposed model represents a significant stride in biometric technology, offering secure, non-intrusive user identification through the synergy of behavior biometrics and emerging modalities.
27
Kobat, Mehmet Ali, and Turker Tuncer. "Coronary Angiography Print: An Automated Accurate Hidden Biometric Method Based on Filtered Local Binary Pattern Using Coronary Angiography Images." Journal of Personalized Medicine 11, no. 10 (October 1, 2021): 1000. http://dx.doi.org/10.3390/jpm11101000.
Full textAbstract:
Background and purpose: Biometrics is a commonly studied research issue for both biomedical engineering and forensics sciences. Besides, the purpose of hidden biometrics is to discover hidden biometrics features. This work aims to demonstrate the biometric identification ability of coronary angiography images. Material and method: A new coronary angiography images database was collected to develop an automatic identification model. The used database was collected from 51 subjects and contains 2156 images. The developed model has to preprocess; feature generation using local binary pattern; feature selection with neighborhood component analysis; and classification phases. In the preprocessing phase; image rotations; median filter; Gaussian filter; and speckle noise addition functions have been used to generate filtered images. A multileveled extractor is presented using local binary pattern and maximum pooling together. The generated features are fed to neighborhood component analysis and the selected features are classified using k nearest neighbor classifier. Results: The presented angiography image identification method attained 99.86% classification accuracy on the collected database. Conclusions: The obtained findings demonstrate that the angiography images can be utilized as biometric identification. Moreover, we discover a new hidden biometric feature using coronary angiography images and name of this hidden biometric is coronary angiography print.
28
Omar, Bayan. "Fusion Method with Mean-discrete Algorithm in Feature level for Identical twins Identification." UHD Journal of Science and Technology 4, no. 2 (December 27, 2020): 141. http://dx.doi.org/10.21928/uhdjst.v4n2y2020.pp141-150.
Full textAbstract:
The study on twins is an important form of study in the forensic and biometrics field as twins share similar genetic traits. A biometric is one of the common types of pattern recognition which acquires biometric data from a person. From these data, a feature is established and extracted where these features can be used to identify individual. Exiting works in biometric identification concentrate on unimodal biometric identification. The high similarity in a pair of twin’s biometric may lead to miss performance. Hence, due to their great accurateness, multimodal biometric systems have become more favored than unimodal biometric systems in identical twins identification. However, these systems are highly complex. We proposed Mean-Discrete feature based fusion algorithm for Kurdish handwriting and fingerprint for identical twins detection. Its viability and advantage over the unimodal biometric systems are highlighted. This paper employed 800 images from 50 pairs of identical twins from Kurdistan Region to carry out the experiment.
29
Яна Викторовна, Артамонова. "Biometric technologies: the attitude of the population and overcoming risks." STATE AND MUNICIPAL MANAGEMENT SCHOLAR NOTES 1, no. 1 (March 29, 2024): 231–36. http://dx.doi.org/10.22394/2079-1690-2024-1-1-231-236.
Full textAbstract:
The article is devoted to biometric identification systems. Currently, biometric identification systems are used in various services, replacing systems that use a person's username and password as identifiers. The authors of the work address the social and technological aspects of biometrics in the framework of the article. The article describes the main types of biometric systems using both static and dynamic methods. The authors also identify the main reasons for skepticism on the part of users among the Russian population, which include citizens' distrust of the reliability of storing personal information, which can lead to data leakage. The article discusses the current problems of using biometric identification systems and their solutions.
30
Yang, Wencheng, Song Wang, Hui Cui, Zhaohui Tang, and Yan Li. "A Review of Homomorphic Encryption for Privacy-Preserving Biometrics." Sensors 23, no. 7 (March 29, 2023): 3566. http://dx.doi.org/10.3390/s23073566.
Full textAbstract:
The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biometric data is a key area of research. Security and privacy are vital to enacting integrity, reliability and availability in biometric-related applications. Homomorphic encryption (HE) is concerned with data manipulation in the cryptographic domain, thus addressing the security and privacy issues faced by biometrics. This survey provides a comprehensive review of state-of-the-art HE research in the context of biometrics. Detailed analyses and discussions are conducted on various HE approaches to biometric security according to the categories of different biometric traits. Moreover, this review presents the perspective of integrating HE with other emerging technologies (e.g., machine/deep learning and blockchain) for biometric security. Finally, based on the latest development of HE in biometrics, challenges and future research directions are put forward.
31
Mróz-Gorgoń, Barbara, Wojciech Wodo, Anna Andrych, Katarzyna Caban-Piaskowska, and Cyprian Kozyra. "Biometrics Innovation and Payment Sector Perception." Sustainability 14, no. 15 (August 1, 2022): 9424. http://dx.doi.org/10.3390/su14159424.
Full textAbstract:
This paper presents an analysis of innovations in the biometrics market, which have started to play a very important role in personal identification and identification systems. The aim of the study was to analyze current customs and opinions regarding payment methods, as well as to identify threats and opportunities for new biometric solutions in this area. First, the history of the biometrics market is presented. Acceptance patterns of new technologies are explored and modified. The authors used literature reviews, qualitative research (focus groups), and quantitative research (questionnaire survey) as methods. The main value and importance of biometrics is the uniqueness of biometric patterns (e.g., face, fingerprint, iris, etc.), which takes the security of these systems to a new level. The results of the quantitative study based on the qualitative survey show positive verification of the hypothesized reasons; e.g., importantly, that the age of potential users of biometric payments influences the fear about personal data. Fear of losing personal data affects the perceived safety of biometric payments. Perceived security has a very strong influence on attitudes towards biometric payments, which is the strongest predictor of behavioral intention to use biometric payments.
32
Елена Юрьевна, Фролова, and Кошлыкова Юлия Александровна. "HUMAN IDENTIFICATION BASED ON BIOMETRIC DATA: A REVIEW OF MODERN TECHNOLOGIES." NORTH CAUCASUS LEGAL VESTNIK 1, no. 3 (September 2022): 167–74. http://dx.doi.org/10.22394/2074-7306-2022-1-3-167-174.
Full textAbstract:
Biometric identification systems have now become quite widespread, since they use not specialized physical media for recognition, but signs or features of the person himself, which makes it possible to reliably identify a person for a given purpose. Biometric identification is the process of comparing and determining the similarity between a person's data and his biometric "template". Biometrics allows you to identify and verify a person based on a set of specific and unique traits inherent in him from birth. This article discusses certain types of biometric data to be identified, problems and prospects of their application.
33
Ali, Nadir, M. Asghar Khattak, Samina Kanwal, Noreen Farid, Shehrbano Batool, and Mufassar Nishat. "Comparison of Forensic Value of Biometric Analysis in Face & Ear Recognition in the Punjabi Population, Pakistan." Pakistan Journal of Medical and Health Sciences 16, no. 12 (December 31, 2022): 614–16. http://dx.doi.org/10.53350/pjmhs20221612614.
Full textAbstract:
Background: The use of face biometrics is very prevalent in forensic investigations for the identification of the perpetrators of crime due to the excessive use of CCTV footage that is usually available at the scene of a crime in urban settings. Ear biometric analysis of ear prints is also in vogue as a result of research advancements in the fields of biometrics. Keeping in view this scenario, it is the need of the hour to analyze the forensic value of this type of forensic evidence and compare these two tools of forensic biometrics. Purpose: To analyze and compare the forensic value of biometric analysis of face and ear print recognitions in the Punjabi population, in Punjab, Pakistan. Study design: This study is conducted by collecting the data from 100 samples of different people belonging to different backgrounds from different cities in Punjab, Pakistan after their informed consent and ethical approval. Their facial photographs and ear prints were collected for proceeding biometric analysis to form a database for comparison and recognition. Method and materials: After collecting data, the comparison is done to see whether we can recognize a person by only using ear print analysis or face biometrics after running a search in our own created database. Moreover, we also calculated the forensic values of this biometric analysis separately on its own and combined these two i.e., face and ear biometrics. . Furthermore, standard deviation, F-statistics, and Chitest p-value were also applied to see the power of discrimination of these two biometric methods of identification Results: In 100 samples, face recognition was proved to be 80 % recognition of identity as compared with only ear prints which showed 56 % accuracy in identifying the individuals who participated in this research. Furthermore, the combined result of both face recognition and ear biometrics showed 90 % recognition of the identity of the individuals. Statistical analysis proved that biometric analysis of the face for recognition of the identity of individuals was more valued as compared with ear print recognition. Also, it was found that if we combine these two methods of biometrics, the forensic value of recognition of individuals has increased and showed good results. Conclusion: The forensic value of biometric evidence of face and ear recognition is a very important tool for the forensic identification of individuals in crime scene investigations. Biometric facial recognition is better as compared to only ear print biometric analysis. Furthermore, using face and ear biometrics enhances the forensic value of biometric analysis. Keywords: Biometric analysis, Forensic value, face recognition, ear print recognition,
34
Venkata Ramudu, Dr Balasani, Mr Chiranjeevi Kondabathini, and Mr Udaya Kiran Mandhugula. "Enhancing Handwritten Signature Identification and Palm Biometric Objectives." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (December 30, 2023): 1–13. http://dx.doi.org/10.55041/ijsrem27802.
Full textAbstract:
Soft biometrics are already widely used as a support tool for user identification. However, it is not the only use for biometric information that is conceivable because such information can be sufficient to obtain minimal details from the user that are unrelated to his identity. Examples of what might be referred to as soft biometrics include gender, hand orientation, and emotional state. Utilizing physiologic modalities for soft-biometric work is extremely prevalent, prediction, but behavioral data is frequently disregarded. Keystroke dynamics and handwriting signature are two potential behavioral modalities that could be used to predict a user's gender, but they are rarely discussed in the literature together. This study seeks to fill this gap by examining the influence of combining these two distinct biometric modalities on the accuracy of gender prediction and the best way. Key Words: Item key-strokes, Bio-metric signatures, digital signs, dynamic temporal wrapping (DTW)
35
Jain, Mradula, and Anshul Khurana. "Overview of Biometric Fingerprint Identification." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 2721–25. http://dx.doi.org/10.31142/ijtsrd14101.
Full text
36
K. P. Ajitha, Gladis, and D. Sharmila. "Systematic digital signal processing approach in various biometric identification." i-manager's Journal on Digital Signal Processing 10, no. 2 (2022): 7. http://dx.doi.org/10.26634/jdp.10.2.19290.
Full textAbstract:
Biometrics are unique physical characteristics, such as fingerprints, that can be used for automatic recognition. Biometric identifiers are often classified as physiological characteristics associated with body shape. The goal is to capture a piece of biometric data from that person. It could be a photograph of their face, a recording of their voice, or a picture of their fingerprints. While there are numerous types of biometrics for authentication, the six most common are facial, voice, iris, near-field communication, palm or finger vein patterns, and Quick Response (QR) code. Biometrics is a subset of the larger field of human identification science. This paper explores computational approaches to speaker recognition, face recognition, speech recognition, and fingerprint recognition to assess the overall state of digital signal processing in biometrics.
37
SAMSON, THEODOR, and ADRIAN IFTENE. "IDENTIFICATION OF ANIMALS OF SIGNIFICANT ZOOTECHNICAL VALUE." European Journal of Public Administration Research, no. 2 (2024): 21–33. http://dx.doi.org/10.47743/ejpar.2023-2-3.
Full textAbstract:
Biometric identification has brought about profound change in a variety of fields, and its enormous potential in zootechnics has attracted considerable interest. The primary purpose of this paper is to explore the practical application of biometric technologies for the purpose of identifying cattle in a unique manner. Utilizing these cutting-edge technologies, the research seeks to develop a comprehensive understanding of how biometrics can be used to establish the unique identity of individual cattle samples.
38
Rai, Ankush, and Jagadeesh Kannan R. "SURVEY OF SOFT BIOMETRIC TECHNIQUES FOR GENDER IDENTIFICATION." Asian Journal of Pharmaceutical and Clinical Research 10, no. 13 (April 1, 2017): 296. http://dx.doi.org/10.22159/ajpcr.2017.v10s1.19741.
Full textAbstract:
Biometrics checks can be productively utilized for localization of intrusion in access control systems by utilizing soft computing frameworks.Biometrics procedures can be to a great extent separated into conventional and soft biometrics. The study presents a survey of the available softtechniques and comparison for gender identification from biometric techniques.
39
Veerasamy, Nanda Kumar. "An analysis of issues in biometric finger identification." International Journal of Engineering & Technology 3, no. 3 (August 28, 2014): 391. http://dx.doi.org/10.14419/ijet.v3i3.2368.
Full textAbstract:
A Person's identity is an essential factor in this vastly connected society. Biometric Finger has wide acceptance as a genuine method for determining an individuals identity. Biometric Finger authentication is reliable, since physical characteristics in humans are difficult to forge, harder to change or make copies. Biometric fingerprinting is one of the most popular and legally accepted biometrics used in person identification. Finger print authentication applications include Computer Applications, Network Access, Data Protection, Transaction Security, and Web Security. E-commerce and E-governments can carry out strong authentication rules. This paper analyzes issues related to Fingerprint identification to suggest viable alternatives. Keywords: Fingerprint Identification, Optical Sensors, Ultrasound Sensors, Issues in Finger Print Identification.
40
Manju, M. "Human body odour as a biometric indicator for person identification." i-manager’s Journal on Pattern Recognition 10, no. 2 (2023): 1. http://dx.doi.org/10.26634/jpr.10.2.20353.
Full textAbstract:
In biometric identification, various physiological and behavioral traits such as fingerprints, facial features, iris patterns, and voice have been extensively explored. This paper introduces human body odour as a biometric trait for person identification. Body odour, composed of volatile organic compounds unique to each individual, presents a challenge for biometric authentication. The study explores the scientific basis of human body odour, including its chemical composition and uniqueness. The paper presents the enrollment process for capturing and storing body odour data, emphasizing the potential of electronic nose (E-nose) devices for scent detection and pattern recognition. This paper discusses the advantages of body odour biometrics, including its resistance to masking by artificial scents and its potential to reduce password administration costs. The proposed odour biometric system offers a non-intrusive and reliable means of person identification, particularly in scenarios where traditional biometric modalities may be impractical or ineffective.
41
S. Raju, A., and V. Udayashankara. "A Survey on Unimodal, Multimodal Biometrics and Its Fusion Techniques." International Journal of Engineering & Technology 7, no. 4.36 (December 9, 2018): 689. http://dx.doi.org/10.14419/ijet.v7i4.36.24224.
Full textAbstract:
Presently, a variety of biometric modalities are applied to perform human identification or user verification. Unimodal biometric systems (UBS) is a technique which guarantees authentication information by processing distinctive characteristic sequences and these are fetched out from individuals. However, the performance of unimodal biometric systems restricted in terms of susceptibility to spoof attacks, non-universality, large intra-user variations, and noise in sensed data. The Multimodal biometric systems defeat various limitations of unimodal biometric systems as the sources of different biometrics typically compensate for the inherent limitations of one another. The objective of this article is to analyze various methods of information fusion for biometrics, and summarize, to conclude with direction on future research proficiency in a multimodal biometric system using ECG, Fingerprint and Face features. This paper is furnished as a ready reckoner for those researchers, who wish to persue their work in the area of biometrics.
42
Nídlová, Veronika, and Jan Hart. "Reliability of Identification Based on Fingerprints in Dual Biometric Identification Systems." Applied Mechanics and Materials 752-753 (April 2015): 1040–44. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1040.
Full textAbstract:
At present, the development of biometrics is a widely discussed topic. This research discusses the reliability of the most used category - identification using fingerprints. There are many of these types of systems. The most affordable, and therefore the most common alternative is one that identifies users using an optical sensor. Testing was conducted on two scanners only for fingerprints, and on two systems that recognize users via their fingerprints and also through a facial image. The conclusions from the measurements were that reliability was mainly affected by the characteristics of the scanners, in particular whether the scanner identifies only based on the fingerprint, or in combination with another biometric method. Due to the fact that with combined systems manufacturers focus only on one identification circuit – usually the most modern - and not the potentially safest, i.e. a fingerprint, the results show that it is much easier to sabotage dual biometric identification devices than those that identify solely on the basis of a fingerprint. Reliability values greatly exceed the values specified by the manufacturer. The measurements show that there is a need to continuously improve dual biometric identification systems.
43
Mashagba, Eman Fares Al. "Human Identification Based on Geometric Feature Extraction Using a Number of Biometric Systems Available: Review." Computer and Information Science 9, no. 2 (May 2, 2016): 140. http://dx.doi.org/10.5539/cis.v9n2p140.
Full textAbstract:
<span style="font-size: 10.5pt; font-family: 'Times New Roman','serif'; mso-ansi-language: EN-US; mso-bidi-font-size: 12.0pt; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Biometric technology has attracted much attention in biometric recognition. Significant online and offline applications satisfy security and human identification based on this technology. Biometric technology identifies a human based on unique features possessed by a person. Biometric features may be physiological or behavioral. A physiological feature is based on the direct measurement of a part of the human body such as a fingerprint, face, iris, blood vessel pattern at the back of the eye, vascular patterns, DNA, and hand or palm scan recognition. A behavioral feature is based on data derived from an action performed by the user. Thus, this feature measures the characteristics of the human body such as signature/handwriting, gait, voice, gesture, and keystroke dynamics. A biometric system is performed as follows: acquisition, comparison, feature extraction, and matching. The most important step is feature extraction, which determines the performance of human identification. Different methods are used for extraction, namely, appearance- and geometry-based methods. This paper reports on a review of human identification based on geometric feature extraction using several biometric systems available. We compared the different biometrics in biometric technology based on the geometric features extracted in different studies. Several biometric approaches have more geometric features, such as hand, gait, face, fingerprint, and signature features, compared with other biometric technology. Thus, geometry-based method with different biometrics can be applied simply and efficiently. The eye region extracted from the face is mainly used in face recognition. In addition, the extracted eye region has more details as the iris features.</span>
44
D S, Dr Dinesh Kumar. "Human Authentication using Face, Voice and Fingerprint Biometrics." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 15, 2021): 853–62. http://dx.doi.org/10.22214/ijraset.2021.36381.
Full textAbstract:
Multimodal biometric approaches are growing in importance for personal verification and identification, since they provide better recognition results and hence improve security compared to biometrics based on a single modality. In this project, we present a multimodal biometric system that is based on the fusion of face, voice and fingerprint biometrics. For face recognition, we employ Haar Cascade Algorithm, while minutiae extraction is used for fingerprint recognition and we will be having a stored code word for the voice authentication, if any of these two authentication becomes true, the system consider the person as authorized person. Fusion at matching score level is then applied to enhance recognition performance. In particular, we employ the product rule in our investigation. The final identification is then performed using a nearest neighbour classifier which is fast and effective. Experimental results confirm that our approach achieves excellent recognition performance, and that the fusion approach outperforms biometric identification based on single modalities.
45
Lozhnikov, Pavel, and Samal Zhumazhanova. "Model of the "biometry-code" converter based on artificial neural networks for analysis of facial thermograms." Digital Technology Security, no. 2 (June 25, 2021): 154–65. http://dx.doi.org/10.17212/2782-2230-2021-2-154-165.
Full textAbstract:
Existing asymmetric encryption algorithms involve the storage of a secret private key, authorized access to which, as a rule, is carried out upon presentation of a password. Passwords are vulnerable to social engineering and human factors. Combining biometric security techniques with cryptography is seen as a possible solution to this problem, but any biometric cryptosystem should be able to overcome the small differences that exist between two different implementations of the same biometric parameter. This is especially true for dynamic biometrics, when differences can be caused by a change in the psychophysiological state of the subject. The solution to the problems is the use of a system based on the "biometrics-code" converter, which is configured to issue a user key after presentation of his/her biometric image. In this case, the key is generated in advance in accordance with accepted standards without the use of biometric images. The work presents results on using thermal images of a user for reliable biometric authentication based on a neural network "biometrics-code" converter. Thermal images have recently been used as a new approach in biometric identification systems and are a special type of biometric images that allow us to solve the problem of both the authentication of the subject and the identification of his psychophysiological state. The advantages of thermal imaging are that this technology is now becoming available and mobile, allowing the user to be identified and authenticated in a non-contact and continuous manner. In this paper, an experiment was conducted to verify the images of thermograms of 84 subjects and the following indicators of erroneous decisions were obtained: EER = 0.85 % for users in the "normal"state.
46
Lai, Chi Qin, Haidi Ibrahim, Shahrel Azmin Suandi, and Mohd Zaid Abdullah. "Convolutional Neural Network for Closed-Set Identification from Resting State Electroencephalography." Mathematics 10, no. 19 (September 22, 2022): 3442. http://dx.doi.org/10.3390/math10193442.
Full textAbstract:
In line with current developments, biometrics is becoming an important technology that enables safer identification of individuals and more secure access to sensitive information and assets. Researchers have recently started exploring electroencephalography (EEG) as a biometric modality thanks to the uniqueness of EEG signals. A new architecture for a convolutional neural network (CNN) that uses EEG signals is suggested in this paper for biometric identification. A CNN does not need complex signal pre-processing, feature extraction, and feature selection stages. The EEG datasets utilized in this research are the resting state eyes open (REO) and the resting state eyes closed (REC) EEG. Extensive experiments were performed to design this deep CNN architecture. These experiments showed that a CNN architecture with eleven layers (eight convolutional layers, one average pooling layer, and two fully connected layers) with an Adam optimizer resulted in the highest accuracy. The CNN architecture proposed here was compared to existing models for biometrics using the same dataset. The results show that the proposed method outperforms the other task-free paradigm CNN biometric identification models, with an identification accuracy of 98.54%.
47
K. Selsiya, Dr. D. Banumathy, Nijanthan, and Dr. G. Madasamyraja. "Person Authentication System Using Multimodal Biometrics." International Journal of Scientific Research in Science, Engineering and Technology 11, no. 3 (May 31, 2024): 276–80. http://dx.doi.org/10.32628/ijsrset24113129.
Full textAbstract:
Biometrics is the automated process used to recognize human by measuring their behavioural and physiological characteristics. Biometrics are generally used either for verification The use of biometric for identification purposes requires that a particular biometric factor be unique for each individual that it can be calculated, and that it is invariant over time. Biometrics such as signatures, photographs, fingerprints, voiceprints and retinal blood vessel patterns all have noteworthy drawbacks. Although signatures and photographs are cheap and easy to obtain and store, they are impossible to identify automatically with assurance, and are easily forget. Human iris on the other hand as an internal organ of the eye and as well protected from the external environment, yet it is easily visible from within one meter of distance makes it a perfect biometric for an identification system with the ease of speed, reliability and automation Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on images of the irises of an individual’s eyes, whose complex random patterns are unique. Proposed system provides a comprehensive implementation of periocular biometrics and a deep insight of various aspects such as utility of peri-ocular region In this project face and eye points are captured using Grassmann algorithm and Gabor filter for eye features extraction. Each trait is analysed separately and given its own score. The results are combined using deep leaning algorithm to provide a single decision in real time environments.
48
Kumar, Sunil. "ECG Biometric Identification." International Journal for Research in Applied Science and Engineering Technology 6, no. 3 (March 31, 2018): 2148–52. http://dx.doi.org/10.22214/ijraset.2018.3505.
Full text
49
de Luis-Garcı́a, Rodrigo, Carlos Alberola-López, Otman Aghzout, and Juan Ruiz-Alzola. "Biometric identification systems." Signal Processing 83, no. 12 (December 2003): 2539–57. http://dx.doi.org/10.1016/j.sigpro.2003.08.001.
Full text
50
Ammour, Basma, Larbi Boubchir, Toufik Bouden, and Messaoud Ramdani. "Face–Iris Multimodal Biometric Identification System." Electronics 9, no. 1 (January 1, 2020): 85. http://dx.doi.org/10.3390/electronics9010085.
Full textAbstract:
Multimodal biometrics technology has recently gained interest due to its capacity to overcome certain inherent limitations of the single biometric modalities and to improve the overall recognition rate. A common biometric recognition system consists of sensing, feature extraction, and matching modules. The robustness of the system depends much more on the reliability to extract relevant information from the single biometric traits. This paper proposes a new feature extraction technique for a multimodal biometric system using face–iris traits. The iris feature extraction is carried out using an efficient multi-resolution 2D Log-Gabor filter to capture textural information in different scales and orientations. On the other hand, the facial features are computed using the powerful method of singular spectrum analysis (SSA) in conjunction with the wavelet transform. SSA aims at expanding signals or images into interpretable and physically meaningful components. In this study, SSA is applied and combined with the normal inverse Gaussian (NIG) statistical features derived from wavelet transform. The fusion process of relevant features from the two modalities are combined at a hybrid fusion level. The evaluation process is performed on a chimeric database and consists of Olivetti research laboratory (ORL) and face recognition technology (FERET) for face and Chinese academy of science institute of automation (CASIA) v3.0 iris image database (CASIA V3) interval for iris. Experimental results show the robustness.