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Gotowe bibliografie tematyczne / PALM PRINT RECOGNITION

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Artykuły w czasopismach

Gotowa bibliografia na temat „PALM PRINT RECOGNITION”

Autor: Grafiati

Data publikacji: 11 września 2023

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Artykuły w czasopismach na temat "PALM PRINT RECOGNITION"

1

Goh, Michael K. O., Connie Tee, and Andrew B. J. Teoh. "BI-MODAL PALM PRINT AND KNUCKLE PRINT RECOGNITION SYSTEM." Journal of IT in Asia 3, no. 1 (2016): 85–106. http://dx.doi.org/10.33736/jita.37.2010.

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This paper proposed an innovative contact-less palm print and knuckle print recognition system. Palm print is referred to as line textures, which contains principal lines, wrinkles and ridges on the inner surface of the palm. On the other hand, knuckle print is denoted as the flexion lines on the inner skin of the knuckles of the fingers. These line patterns are unique and stable, and they offer abundance of useful information for personal recognition. We present a novel palm print and knuckle print tracking approach to automatically detect and capture these features from low resolution video

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2

AlShemmary, Ebtesam. "Siamese Network-Based Palm Print Recognition." Journal of Kufa for Mathematics and Computer 10, no. 1 (2023): 108–18. http://dx.doi.org/10.31642/jokmc/2018/100116.

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palm print recognition is a biometric technology used to identify individuals based on their unique comfort patterns. Identifying patterns in computer vision is a challenging and interesting problem. It is an effective and reliable method for authentication and access control. In recent years, deep learning approaches have been used for handprint recognition with very good results. We suggest in this paper, a Siamese network-based approach for handprint recognition. The proposed approach consists of two convolutional neural networks (CNNs) that share weights and are trained to extract features

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3

Pushpa, N. B., and N. B. Prajwala. "A Scientific Analysis to Observe Uniqueness in Lip Print Pattern." International Journal of Innovative Technology and Exploring Engineering 10, no. 4 (2021): 196–98. http://dx.doi.org/10.35940/ijitee.d8571.0210421.

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Every individual have their unique identification like palm print, signature, finger print, face recognition, lip print etc.. here in this research one such effort is made to analyses lip print and identify the individual using their lip print. The wrinkle and grooves pattern on the lips has individual characteristics like tongue prints, face recognition, iris pattern, fingerprints. Cheiloscopy is a forensic investigation technique that deals with identification of humans based on lips traces. Image processing technique is used, lip print of the individual is captured, processed and analyzed f

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4

Karar, Subhajit, and Ranjan Parekh. "Palm Print Recognition using Zernike Moments." International Journal of Computer Applications 55, no. 16 (2012): 15–19. http://dx.doi.org/10.5120/8839-3069.

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5

Su, Ching-Liang. "Palm-print recognition by matrix discriminator." Expert Systems with Applications 36, no. 7 (2009): 10259–65. http://dx.doi.org/10.1016/j.eswa.2009.01.052.

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6

Badrinath, G. S., and Phalguni Gupta. "Stockwell transform based palm-print recognition." Applied Soft Computing 11, no. 7 (2011): 4267–81. http://dx.doi.org/10.1016/j.asoc.2010.05.031.

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7

ATTAR SHAGUSTHA BANU and N VINOD KUMAR. "IMPLEMENTATION OF ACCURATE PERSONAL IDENTIFICATION BY USING PALM PRINT IMAGE PROCESSING." international journal of engineering technology and management sciences 7, no. 1 (2023): 120–30. http://dx.doi.org/10.46647/ijetms.2023.v07i01.020.

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Online palmprint recognition and latent palmprint identification are two branches of palmprint studies. The former uses middle-resolution images collected by a digital camera in a well-controlled or contact-based environment with user cooperation for commercial applications and the latter uses highresolution latent palmprints collected in crime scenes for forensic investigation. However, these two branches do not cover some palmprint images which have the potential for forensic investigation. Due to the prevalence of smartphone and consumer camera, more evidence is in the form of digital image

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8

Mustafa, Raniah Ali, Haitham Salman Chyad, and Rafid Aedan Haleot. "Palm print recognition based on harmony search algorithm." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 5 (2021): 4113. http://dx.doi.org/10.11591/ijece.v11i5.pp4113-4124.

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Due to its stabilized and distinctive properties, the palmprint is considered a physiological biometric. Recently, palm print recognition has become one of the foremost desired identification methods. This manuscript presents a new recognition palm print scheme based on a harmony search algorithm by computing the Gaussian distribution. The first step in this scheme is preprocessing, which comprises the segmentation, according to the characteristics of the geometric shape of palmprint, the region of interest (ROI) of palmprint was cut off. After the processing of the ROI image is taken as input

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9

Jaafar, Haryati, Salwani Ibrahim, and Dzati Athiar Ramli. "A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier." Computational Intelligence and Neuroscience 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/360217.

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Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI) extraction method were discussed. A sliding neighborhood operation with local histogram equalization

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10

Michael, Goh Kah Ong, Tee Connie, and Andrew Teoh Beng Jin. "An innovative contactless palm print and knuckle print recognition system." Pattern Recognition Letters 31, no. 12 (2010): 1708–19. http://dx.doi.org/10.1016/j.patrec.2010.05.021.

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