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A Line Feature Extraction Method for Finger-Knuckle-Print Verification

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Abstract

Due to its mobility and reliability, the outer finger-knuckle-print (FKP) possesses several advantages over other biometric traits of the hand. However, most existing state-of-the-art methods utilize either local features alone or together with global features for FKP verification. These methods often demand high computational cost despite their high verification accuracy. In this paper, we propose a novel and fast matrix projection method for extracting line features from the finger-knuckle-print for person verification. Essentially, both the horizontal and the vertical knuckle lines are extracted by projecting the knuckle print image onto a shift-and-difference matrix. Such a matrix enables directional image shifting and subtraction within a single matrix multiplication. The resultant difference image then goes through a sigmoidal activation for contrast enhancement. Subsequently, the Fourier spectrum of the contrast enhanced image is adopted as the holistic features of the given finger-knuckle-print image. The entire process of extracting the proposed features is expressed in an analytic form to facilitate a fast vectorized implementation. For cognition performance enhancement, the two directional line features are subsequently fused at the score level by minimizing the error counts of the extreme learning machine kernel. Extensive experiments are performed to compare the proposed method with competing methods using three public finger-knuckle-print databases. Our experimental results show encouraging performance in terms of verification accuracy and computational efficiency.

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Notes

  1. Although the authors of [20] have named a fourth group, namely, the “other image processing approach,” no reference can be found to fall under such a group. Moreover, we found that the first three groups are enough to cover all the existing works in the literature. Based on these observations, the fourth group is excluded in our categorization.

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Acknowledgments

The authors are thankful to the associate editor and the anonymous reviewers for their constructive comments to improve the paper.

Funding

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant number: NRF-2015R1D1A1A09061316).

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Republic of Korea

    Jooyoung Kim, Kangrok Oh & Kar-Ann Toh

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore

    Beom-Seok Oh & Zhiping Lin

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  1. Jooyoung Kim
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  2. Kangrok Oh
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Correspondence to Kar-Ann Toh.

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Kim, J., Oh, K., Oh, BS. et al. A Line Feature Extraction Method for Finger-Knuckle-Print Verification. Cogn Comput 11, 50–70 (2019). https://doi.org/10.1007/s12559-018-9593-6

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