Journal Title : International Journal of Modern Trends in Engineering and Science
Paper Title : PALMPRINT RECOGNITION: MULTI-BIOMETRIC AUTHENTICATION SYSTEM USING LEFT AND RIGHT PALMPRINT COMBINED WITH PASSWORD VERIFICATION
Volume 03 Issue 11 2016
ISSN no: 2348-3121
Page no: 22-25
Abstract – Biometrics is used for automatic identification of human based on their physical and/or behavioral characteristics that present some specific properties such as, uniqueness and permanence. Palmprint is one the unique feature that can be used in personal identification. The proposed system operates in two phases, in the first phase the principal lines from left, right and reverse right palmprint are extracted using Haar Discrete Wavelet Transform method and a matching score is obtained. Based on the score the query palmprint is matched. In the second phase the minutiae features are extracted and compared for the left and right palmprint separately. When the palmprint is matched, password verification is done as a two factor authentication. Multi-biometrics outperforms single biometrics for authentication, hence both the left and right palmprint combined with password verification is used for authentication.
Keywords— Palmprint; Biometrics; Principal lines; Minutiae
- Ahmadyfard, A and Nosrati, M.S. “A Novel Approach for Fingerprint Singular Points Detection Using 2D-wavelet”, In proceedings of IEEE/ACS International conference on Computer Systems and Applications, May 13-16 , pp.688-691,2007.
- Chih-Lung Lin, Shih-Hung Wang, Hsu-Yung Cheng, Kuo-Chin Fan , Wei-Lieh Hsu and Chin-Rong Lai., “Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images”, Sensors 2015, 15, 31339-31361.
- Chin, Y.J., Ong, T.S., Goh, M.K.O., Bee Yan Hiew., “Integrating palmprint and fingerprint for identity verification”, Proc of the 3rd International Conference on Network and System, Security, 2009:437-442.
- D. Huang, W. Jia, and D. Zhang, “Palmprint Verification Based on Principal Lines”, Pattern Recognition, vol. 41, no. 4, pp. 1316-1328, 2008.
- Dr .Ekbal H. Ali, Dr. Ekhlas H. Karam, Dr. Ekhlas H. Karam, “Fingerprint Recognition Using Discrete Wavelet Transform, And Neural Network For Estimation Rotation Region, Journal of Engineering and Development”, Vol. 18, No.3 , May 2014.
- Hafiz Imtiaz, Shaikh Anowarul Fattah, “A Wavelet-based Feature Selection Scheme for Palm-print Recognition”, International Journal of Modern Engineering Research (IJMER), Vol.1, Issue.2, pp-278-287, July 2013.
- Jifeng Dai and Jie Zhou, Multifeature-Based High-Resolution Palmprint Recognition, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 33, No. 5, May 2011.
- Jifeng Dai, Jianjiang Feng, Jie Zhou, Robust and Efficient Ridge-Based Palmprint Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, No. 8, August 2012.
- R. C. Gonzalez, R. E. Woods, and S. L. Eddins: “Digital Image Processing Using Matlab”, 1st Indian Reprint, Pearson Education, 2004.
- Sakshi Kalra et al, “A Survey on Multimodal Biometric”, International Journal of Computer Science and Information Technologies, Vol. 5 (2), 2014, 2148-2151.
- Yong Xu , QiZhu, David Zhang, “Combine crossing matching scores with conventional matching scores for bimodal biometrics and face and palmprint recognition experiments”, Neurocomputing 74(2011)3946-3952, August 2011.
- Yong Xu, Lunke Fei, and David Zhang, “Combining Left and Right Palmprint Images for More Accurate Personal Identification”, IEEE Transactions on Image Processing, Vol. 24, No. 2, February 2015.
- Zhang, D., Zuo, W., and Yue, F., “A comparative study of palmprint recognition algorithms”, ACM Comput. Surv. 44, 1, Article 2, January 2012.
- Zhenan Sun, Libin Wang, and Tieniu Tan, “Ordinal Feature Selection for Iris and Palmprint Recognition”, Volume:23, Issue:9, July 2014.