Fast and efficient difference of block means code for palmprint recognition

Author:

Almaghtuf Jumma,Khelifi FouadORCID,Bouridane Ahmed

Abstract

AbstractOver the past two decades, researchers in the field of biometrics have presented a wide variety of coding-based palmprint recognition methods. These approaches mainly rely on extracting the texture features, e.g. line orientations, and phase information, using different filters. In this paper, we propose a new efficient palmprint recognition method based on the Different of Block Means. In the proposed scheme, only basic operations (i.e. mainly additions and subtractions) are used, thus involving a much lower computational cost when compared with existing systems. This makes the system suitable for online palmprint identification and verification. Furthermore, the technique has been shown to deliver superior performance over related systems.

Funder

Northumbria University

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference31 articles.

1. Kong, A., Zhang, D., Kamel, M.: Palmprint identification using feature-level fusion. Pattern Recognit. 39(3), 478–487 (2006)

2. Zhang, D., Kong, W.K., You, J., Wong, M.: Online palmprint identification. IEEE Trans. Pattern Anal. Mach. Intel. 25(9), 1041–1050 (2003)

3. Zhenan, S., Tieniu, T., Yunhong, W., Li. S.Z.: Ordinal palmprint represention for personal identification. In: IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’05), vol. 1, pp. 279–284, June 2005

4. Xiang-Qian, W., Kuan-Quan, W., Zhang, D.: Wavelet based palm print recognition. Intern. Conf. Mach. Learn. Cybern. 3, 1253–1257 (2002)

5. Boles, W.W., Chu, S.Y.T.: Personal identification using images of the human palm. IEEE Annual Conf. Speech Image Technol. Comput. Telecommun. 1, 295–298 (1997)

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