Relevant bibliographies by topics / Reverse image search

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Reverse image search'

Author: Grafiati
Published: 28 June 2021
Last updated: 25 April 2022

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Journal articles on the topic "Reverse image search"

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Al-Lohibi, Hanaa, Tahani Alkhamisi, Maha Assagran, Amal Aljohani, and Asia Othaman Aljahdali. "Awjedni: A Reverse-Image-Search Application." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 9, no. 3 (September 13, 2020): 49–68. http://dx.doi.org/10.14201/adcaij2020934968.

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The abundance of photos on the internet, along with smartphones that could implement computer vision technologies allow for a unique way to browse the web. These technologies have potential used in many widely accessible and globally available reverse-image search applications. One of these applications is the use of reverse-image search to help people finding items which they're interested in, but they can’t name it. This is where Awjedni was born. Awjedni is a reverse-image search application compatible with iOS and Android smartphones built to provide an efficient way to search millions of products on the internet using images only. Awjedni utilizes a computer vision technology through implementing multiple libraries and frameworks to process images, recognize objects, and crawl the web. Users simply upload/take a photo of a desired item and the application returns visually similar items and a direct link to the websites that sell them.
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Katasani, S. R., T. Rachepalli, N. Kamat, and M. Jadhav. "Similar Fashion Finder using Reverse Image Search." International Journal of Computer Sciences and Engineering 7, no. 5 (May 31, 2019): 1190–95. http://dx.doi.org/10.26438/ijcse/v7i5.11901195.

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Sharifzadeh, Afsheen, and Gideon P. Smith. "Inaccuracy of Google reverse image search in complex dermatology cases." Journal of the American Academy of Dermatology 84, no. 1 (January 2021): 202–3. http://dx.doi.org/10.1016/j.jaad.2020.04.107.

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Araujo, Flavio H. D., Romuere R. V. Silva, Fatima N. S. Medeiros, Dilworth D. Parkinson, Alexander Hexemer, Claudia M. Carneiro, and Daniela M. Ushizima. "Reverse image search for scientific data within and beyond the visible spectrum." Expert Systems with Applications 109 (November 2018): 35–48. http://dx.doi.org/10.1016/j.eswa.2018.05.015.

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Lin, JianPu, WeiXing Wang, JianMin Yao, TaiLiang Guo, Enguo Chen, and Qun Frank Yan. "Fast multi-view image rendering method based on reverse search for matching." Optik 180 (February 2019): 953–61. http://dx.doi.org/10.1016/j.ijleo.2018.12.003.

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Zhang, Ke, and Zhao Gao. "The Technology of Fast 3D Reconstruction Based on Stereo Vision." Key Engineering Materials 579-580 (September 2013): 654–58. http://dx.doi.org/10.4028/www.scientific.net/kem.579-580.654.

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Reverse engineering has become an independent research area in CAD/CAM system with the development of modern manufacturing. The 3D reconstruction technology of generating a digit model from physical model is an important part of reverse engineering. The 3D reconstruction technology based on stereo vision has advantages such as non-contact measurement, simple system structure, being fast and efficient. In this paper, a fast 3D reconstruction technology based on stereo vision is presented. Firstly, BP neural network is used to simulate the mapping relationship between the 3D object and its images. Then, the epipole positions and adjusting coefficients for epipolar lines are calculated according to the epipolar line constraint. After the rectification transformations on the left and right image planes is conducted, the pairs of conjugate epipolar lines become collinear and parallel to the horizontal image axis. Therefore, when the stereo correspondences between the left and right images are being performed, the search is done only along the horizontal lines of the rectified images, which is highly advantageous to fast image matching for stereo vision and 3D reconstruction of free-form surface.
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Amerini, Irene, Rudy Becarelli, Roberto Caldelli, and Matteo Casini. "A Feature-Based Forensic Procedure for Splicing Forgeries Detection." Mathematical Problems in Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/653164.

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Nowadays, determining if an image appeared somewhere on the web or in a magazine or is authentic or not has become crucial. Image forensics methods based on features have demonstrated so far to be very effective in detecting forgeries in which a portion of an image is cloned somewhere else onto the same image. Anyway such techniques cannot be adopted to deal with splicing attack, that is, when the image portion comes from another picture that then, usually, is not available anymore for an operation of feature match. In this paper, a procedure in which these techniques could also be employed will be shown to get rid of splicing attack by resorting to the use of some repositories of images available on the Internet like Google Images or TinEye Reverse Image Search. Experimental results are presented on some real case images retrieved on the Internet to demonstrate the capacity of the proposed procedure.
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Hokka, Jenni, and Matti Nelimarkka. "Affective economy of national-populist images: Investigating national and transnational online networks through visual big data." New Media & Society 22, no. 5 (August 21, 2019): 770–92. http://dx.doi.org/10.1177/1461444819868686.

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In our article, we investigate the affective economy of national-populist image circulation on Facebook. This is highly relevant, since social media has been an essential area for the spread of national-populist ideology. In our research, we analyse image circulation as affective practice, combining qualitative and quantitative methods. We use computational data analysis methods to examine visual big data: image fingerprints and reverse image search engines to track down the routes of thousands of circulated images as well as make discourse-historical analysis on the images that have gained most attention among supporters. Our research demonstrates that these existing tools allow social science research to make theory-solid approaches to understand the role of image circulation in creating and sustaining national and transnational networks on social media, and show how national-populist thinking is spread through images that catalyse and mobilise affects – fear, anger and resentment – thus creating an effective affective economy.
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Reitelshöfer, Sebastian, Sebastian Meister, and Jörg Franke. "Recognition and Description of Unknown Everyday Objects by Using an Image Based Meta-Search Engine for Service Robots." Advanced Engineering Forum 19 (October 2016): 132–38. http://dx.doi.org/10.4028/www.scientific.net/aef.19.132.

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In future applications service robots will operate in complex and unstructured environments. While performing daily tasks such systems will have to recognize many different unknown objects in order to be able to conduct continuative processes. To support enhanced functionalities of a service robot system an image based meta-search engine that is accessible for a machine can be used. In this contribution the realization of an approach to determine reasonable identification results for single and multiple everyday objects by using the Google reverse image search system is described. In order to deliver convenient results for the communication of a robotic system with a human user the generated search results are post-processed and prepared in order to provide reasonable object descriptions. To enable an intuitive application, control a gesture based approach allows potential users to initialize a search procedure by pointing at an object of interest while being observed by a camera system. The performed experiments show a quite reliable detection behavior for a reasonably broad variety of everyday objects.
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Kunash, А. А. "Interpretation, topography and chronology of the greco-catholic medals of the XVII–XVIII centuries (according to archaeological research and analysis of private collections)." Proceedings of the National Academy of Sciences of Belarus, Humanitarian Series 66, no. 1 (February 25, 2021): 41–57. http://dx.doi.org/10.29235/2524-2369-2021-66-1-41-57.

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The article provides an analysis and interpretation of 55 Greek Catholic medals of the 17th – 18th centuries. The search for information about Greek Catholic medals was carried out through the study of scientific literature, search in catalogs of private collections, monitoring of specialized sites dedicated to the subjects of Christian worship and Internet forums of “black” diggers, as well as Internet auctions. During archaeological research, only 4 Greek Catholic medals were identified (Belarus, Lithuania, Poland, Italy). The overwhelming majority of the medals under consideration (51 copies) were discovered during the illegal work of “black archaeologists” in Belarus, Ukraine, Poland and Spain. On the front side, the Greek Catholic medals contain images of the Mother of God Zhirovitskaya, Mother of God of Pochaev, Mother of God of Kholmskaya and Mother of God of Borunskaya. On the reverse side there are images of St. Andrew (apostle), St. Basil the Great, St. Joseph with the Christ Child, St. Josaphat Kuntsevich, St. Anufriy the Great. Most of the medals are labeled in Latin. The inscriptions on the medals with the image of Our Lady of Zhirovitskaya (subtype 3 (no. 5–26)) are made from a set of letters of the Greek, Latin and Church Slavonic alphabets.
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Dissertations / Theses on the topic "Reverse image search"

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Jurečka, Tomáš. "Detekce a klasifikace létajících objektů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442512.

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The thesis deals with the detection and classification of flying objects. The work can be divided into three parts. The first part describes the creation of dataset of flying objects. The reverse image search is used to create the dataset. The next part is a research of algorithms for detection, tracking and classification. Subsequently, the individual algorithms are applied and evaluated. In the last part, the design of hardware components is performed.
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Carvalho, José Ricardo de Abreu. "Pesquisa multimodal de imagens em dispositivos móveis." Master's thesis, 2021. http://hdl.handle.net/10400.13/3984.

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Apesar das evoluções no campo de Reverse Image Search, com algoritmos cada vez mais robustos e eficazes, continua a haver interesse para que as técnicas de pesquisa possam ser aprimoradas, melhorando a experiência do utilizador na procura das imagens que tem em mente. O objetivo principal deste trabalho foi desenvolver uma aplicação para dispositivos móveis (smartphones) que permitisse ao utilizador encontrar imagens através de inputs multimodais. Assim, esta dissertação, para além de propor pesquisas por diversos modos (palavras-chave, desenho, e imagens da câmara ou existentes no dispositivo), propõe que o utilizador consiga criar uma imagem por si só através de desenho, ou editar/alterar uma imagem existente, tendo feedback no momento aquando de cada alteração/interação. Ao longo da experiência de pesquisa, o utilizador consegue usar as imagens encontradas (que achar relevantes) e ir aprimorando a pesquisa através dessa edição, indo de encontro ao que pensa encontrar. A implementação desta proposta teve como base a Cloud Vision API da Google responsável pela obtenção dos resultados através do input de imagem, a Google Custom Search API para a obtenção de imagens através do input por texto, e a framework ATsketchkit que permitia a criação de desenho, para o sistema iOS da Apple. Foram realizados testes com um conjunto de utilizadores com diversos níveis de experiência em pesquisa de imagens e na habilidade de desenho, permitindo aferir a preferência nos diferentes métodos de input, a satisfação na obtenção dos resultados, bem como da usabilidade do protótipo.
Despite the evolution in the field of reverse image search, with algorithms becoming more robust and effective, there still interest for improving search techniques, improving the user experience when searching for the images the user has in mind. The main goal of this work was to develop an application for mobile devices (smartphones) that would allow the user to find images through multimodal inputs. Thus, this dissertation, in addition to propose the search for images in different ways (keywords, drawing/sketching, and camera or device images), proposes that the user can create an image by himself through drawing, editing / changing an existing image, having feedback at the time of each change / interaction. Throughout the search experience, the user can use the images found (which it finds relevant) and improve the search through its edition, going against what it thinks to find. The implementation of this proposal was based on a Google Cloud Vision API responsible for obtaining the results, and the ATsketchkit framework that allowed the creation of drawings, for Apple's iOS system. Tests were carried out with a set of users with different levels of experience in image research and different drawing ability, allowing to assess preference in different input methods, satisfaction with the images retrieved, as well as the usability of the prototype.
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Book chapters on the topic "Reverse image search"

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O’Neil, Fer. "Looking Forward to Reverse Image Search: Measuring the Effectiveness of Reverse Image Searches in Online Help." In Advances in Intelligent Systems and Computing, 24–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60477-0_3.

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Kansara, Dhvani, Aditya Shinde, Yashi Suba, and Abhijit Joshi. "Optimizing Reverse Image Search by Generating and Assigning Suitable Captions to Images." In Algorithms for Intelligent Systems, 621–31. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3242-9_59.

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Wu, Dan, Chenyang Zhang, Abidan Ainiwaer, and Siyu Lv. "Hybrid Research on Relevance Judgment and Eye Movement for Reverse Image Search." In Diversity, Divergence, Dialogue, 211–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71292-1_19.

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Skelchy, Russell P. "Beyond Black and Gray." In Vamping the Stage. University of Hawai'i Press, 2017. http://dx.doi.org/10.21313/hawaii/9780824869861.003.0013.

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Female performers in Indonesia have long held a socially ambiguous status—maligned for associations with sexual freedom and prostitution, or else revered for their mystical and supernatural powers. Often confined by negative labels, they negotiate identity somewhere between stereotypes attributed to them and one they desire for themselves. This chapter focuses on Waljinah, an Indonesian icon and keroncong’s most renowned vocalist. The trajectory of her career has coincided with an important era of modernization in Indonesia, especially as it searched for ways to unify its diverse population under a “national culture.” Keroncong, considered by early Indonesian nationalists to be a musical lingua franca bridging ethnic groups, continued to have an important role in the post-independence Sukarno era and subsequent New Order regime. As a popular female keroncong vocalist during this period, depictions of Waljinah in print media also reflected state sanctioned ideas about what constituted the “modern Indonesian woman.” This study explores how genderings and gender ideologies were employed through specific types of language and discourse to create differing images of Waljinah while discussing tactics she has used manage and control how she is portrayed in the mass media.
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Conference papers on the topic "Reverse image search"

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Singh, Paras Nath, and Tara P. Gowdar. "Reverse Image Search Improved by Deep Learning." In 2021 IEEE Mysore Sub Section International Conference (MysuruCon). IEEE, 2021. http://dx.doi.org/10.1109/mysurucon52639.2021.9641572.

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Horváth, András. "Object recognition based on Google's reverse image search and image similarity." In Seventh International Conference on Graphic and Image Processing, edited by Yi Xie, Yulin Wang, and Xudong Jiang. SPIE, 2015. http://dx.doi.org/10.1117/12.2228505.

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Bitirim, Yiltan, Selin Bitirim, Duygu Celik Ertugrul, and Onsen Toygar. "An Evaluation of Reverse Image Search Performance of Google." In 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2020. http://dx.doi.org/10.1109/compsac48688.2020.00-65.

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Chutel, Pushpa M., and Apeksha Sakhare. "Evaluation of compact composite descriptor based reverse image search." In 2014 International Conference on Communications and Signal Processing (ICCSP). IEEE, 2014. http://dx.doi.org/10.1109/iccsp.2014.6950085.

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Zhang, Jiajie, Bingsheng Zhang, and Jiancheng Lin. "Recessive Social Networking: Preventing Privacy Leakage against Reverse Image Search." In 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE, 2019. http://dx.doi.org/10.1109/eurospw.2019.00030.

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Mawoneke, Kudzai Felix, Xin Luo, Youqin Shi, and Kenji Kita. "Reverse Image Search for the Fashion Industry Using Convolutional Neural Networks." In 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP). IEEE, 2020. http://dx.doi.org/10.1109/icsip49896.2020.9339350.

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Diyasa, I. Gede Susrama Mas, Alfath Daryl Alhajir, Amir Muhammad Hakim, and Moh Fathur Rohman. "Reverse Image Search Analysis Based on Pre-Trained Convolutional Neural Network Model." In 2020 6th Information Technology International Seminar (ITIS). IEEE, 2020. http://dx.doi.org/10.1109/itis50118.2020.9321037.

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"Workshop: Information Search & Discovery, Using an Image as Query." In InSITE 2019: Informing Science + IT Education Conferences: Jerusalem. Informing Science Institute, 2019. http://dx.doi.org/10.28945/4334.

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Aim/Purpose: This contribution is a tutorial workshop on searching and finding information by using an image as query. Also related topics are addressed. Participants learn about state-of-the-art applications and limitations of reverse image search on the internet and WWW. So they will be motivated and enabled to apply this relatively new method to discover information and to support other potential users. Methodology: This workshop is mainly a long lecture illustrated with practical examples. Interactions with the participants make the session more dynamic. Each participant can also execute practical tests, using a computer and internet.
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Sai, Y. Venkata, Salman, and T. Sasikala. "An In-Depth Look at the Images for Finding Information using Deep learning and Reverse Image Search." In 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2021. http://dx.doi.org/10.1109/icoei51242.2021.9452817.

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Gandini, Martina, and Suela Ruffa. "A DOE Approach for Sensitivity Analysis of a Shape Partitioning Algorithm." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59175.

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In the field of geometrical product specification and verification, one of the main problems is classification and segmentation of 3D shapes. Shape recognition and segmentation is a widespread research area with different application fields (image processing, shape searching, pattern recognition, reverse engineering, etc.). Many methodologies and algorithms have been developed within such different fields, each one exhibiting optimized performances with respect to the set of objects and targets in each application [1, 11, 12]. Nevertheless, for manufactured parts a unique description of shape during the whole product lifecycle is still envisaged, and GPS (“Geometrical Product Specification and Verification”) project seems to be the most promising approach, but it should be stated that the partitioning process is still to be improved both theoretically and operationally. The ISO Technical Committee 213 (TC213), entrusted to develop the GPS project, founded the partitioning process on the classification of shapes based on symmetrical properties of surfaces [5, 6]. The aim of this paper is to describe the method proposed by Gelfand and Guibas [4] and analyze its performances on sampled surfaces by varying parameters of the method that basically affect its efficiency. In fact, the ISO research is currently devoted to identify a segmentation method characterized by efficiency, reliability, robustness and applicability with the aim to standardize the methodology for the verification phase of the manufacturing process. In this paper, a DOE analysis has been performed, in order to search an optimal parameter configuration, necessary to consider the method as a standard for shape partitioning.
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