Palm Print Recognition Using Texture and Shape Features

International Journal of Computer Science and Engineering

© 2022 by SSRG - IJCSE Journal

Volume 9 Issue 2

Year of Publication : 2022

Authors : M. Rajeshwari, K. Rathika

10.14445/23488387/IJCSE-V9I2P101

How to Cite?

M. Rajeshwari, K. Rathika, "Palm Print Recognition Using Texture and Shape Features," SSRG International Journal of Computer Science and Engineering , vol. 9,  no. 2, pp. 1-5, 2022. Crossref, https://doi.org/10.14445/23488387/IJCSE-V9I2P101

Abstract:

Image Processing techniques are used to perform some operations on a digital image to get an enhanced image or extract some features. The biometric system is used everywhere for security and personal identification in today's world. This paper aims to present palm print recognition using image processing techniques. To improve the efficiency of image recognition, during the pre-processing stage, an image must be resized and converted into another colour space. After preprocessing, the retrieved image can be enhanced with the help of a Gaussian filter. The Laplacian of Gaussian technique is used to detect the edges of an image. Then the image is performed using feature extraction methods such as GLCM (Gray Level Co-occurrence Matrix) and Shape and Merged (Texture and Shape) methods. Further, the Statistical measurements are calculated. Euclidean distance is used to retrieve an accurate matching image. The Merged method produces a better result than individual methods. This analysis can be used for criminal, forensic or commercial applications.

Keywords:

Gaussian, LOG, GLCM, Euclidean Distance.

References:

[1] De-Shuang Huang, Wei Jia, and David Zhang,, “Palm Print Verification Based Principal Lines,” Pattern Recognition, vol. 41,
no. 4, pp. 1316-1328, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Komal Kashyap, and Ekta Tamrakar, “Accurate Personal Identification using Left and Right Palmprint Images Based on Anfis
Approach,” International Journal of Mineral Processing and Extractive Metallurgy, vol. 2, no. 2, pp. 13-20, 2017.
[Google Scholar] [Publisher Link]
[3] Zhenan Sun et al., “Ordinal Palm Print Process for Personal Identification,” 2005 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (CVPR'05), vol. 1, 2005.
[CrossRef] [Publisher Link]
[4] Shilpa M, Preethi S, and Dr Suresh L, “Combining Left and Right Palm Print Images for Accurate Identification,” International
Journal of Innovative Research in Computer and Communication Engineering, vol. 4, no. 4, pp. 7976-7983, 2016.
[5] A.K. Jain, and J. Feng, “Latest Palmprint Matching,” IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE, vol.
31, no. 6, pp. 1032-1047, 2009.
[CrossRef] [Publisher Link]
[6] K.Y . Rajput, Melissa Amanna, and Sharma, “Palmprint Recognition using Image Processing,” International Journal of Computing
Science and Communication Techniques, vol. 3, 2011.
[7] Chin-Chuan Han et al., “Personal Authentication using Palm-Print Features,” Pattern Recognition, vol. 36, no. 2, pp. 371-381,
2003.
[CrossRef] [Google Scholar] [Publisher Link]
[8] S. Kanchana, and G.Balakrishnan, “Palm-Print Pattern Matching Based on Features Using Rabin-Karp for Person Identification,”
The Scientific World Journal, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[9] N.B Maheshkumar, and K.Premalatha, “Palmprint Authentication System Based on Local and Global Feature Fusion Using Dost,”
Communications on Applied Electronics, vol. 2014, p.11, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Zhiheng Zhu et al., “Palmprint Image Acquistion and Analysis System Based on IOT Technology,” Open Access Library Journal,
vol. 7, no. 11, pp. 1-8, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Hsne-Ai-Walid et al., “Palm Print Recognition System using Naive Bayes Classifier and Image Processing Tools,”
Communications on Applied Electronics (CAE), vol. 2, no. 6, pp. 45-49, 2015.
[Google Scholar] [Publisher Link]
[12] Dr.T.C. Manjunath, “Detection of Shapes of Objects Using Sophisticated Image Processing Techniques,” International Journal of Computer Science & Emerging Technologies, vol. 1, no. 4, pp. 32-37, 2010.
[Google Scholar]
[13] Liang Wang, and Xin Geng, Behavioral Biometrics for Human Identification, IGI Global Publisher, p.530, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[14] N.V. Boulgouris, Konstantinos N. Plataniotis, and E.M.Tzanakou, Biometrics: Theory, Methods and Applications, WILEY-IEEE Press, p. 600, 2009.
[Google Scholar] [Publisher Link]
[15] Arun A. Ross, Karthik Nandakumar, and Anil K. Jain, Handbook of Multibiometrics, International Series on Biometrics, Springer, 2006.
[Google Scholar] [Publisher Link]
[16] James Wayman et al., Biometric Systems: Technology, Design and Performance Evaluation, Springer, 2004.
[Google Scholar] [Publisher Link]
[17] Samir Nanavati, Michael Thieme, and Raj Nanavati, Biometrics: Identity Verification in a Networked World, John Wiley & Sons, 2002.
[Publisher Link]
[18] Anil Jain, Ruud Bolle, and Sharath Pankanti, Biometrics: Personal Identification in Networked Society, Boston: Kluwer Academic, 1999.
[Publisher Link]
[19] Kasturika B.Ray, and Rachita Mishra, “Palmprint as a Biometric Identifier,” International Journal of Electronics and Communication Technology, vol. 2, no. 3, 2011. [20] D. Zhang et al., “Online Palmprint Identification,” IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 25, vol. 9, 2003.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Nicolae Duta, Anil K. Jain, and Kanti V. Mardia, “Matching of Palmprints,” Pattern Recognition Letters, vol. 23, no. 4, pp. 477-485, 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[22] LI Wen-xin, David Zhang, and XU Zhuo-qun, “Palmprint Recognition Based on Fourier Transform,” Journal of Software, vol. 13, no. 5, pp. 879-886, 2002.
[Google Scholar]
[23] Xiang Qian Wu, Kuan Quan Wang, and Dapeng Zhang, “An Approach to Line Feature Representation and Matching for Palmprint Recognition,” Department of Computing, The Hong Kong Polytechnic University, 2004.
[Google Scholar] [Publisher Link]
[24] A.K. Jain, and N. Duta, “Deformable Matching of Hand Shapes for User Verification,” International Conference on Image Processing, vol. 2, pp. 857-861, 1999. [CrossRef] [Google Scholar] [Publisher Link]