A new class of Zernike moments for computer vision applications
Information Sciences: an International Journal
The identification of users by relational agents
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Hand-based verification and identification using palm-finger segmentation and fusion
Computer Vision and Image Understanding
A survey of biometric technology based on hand shape
Pattern Recognition
Fast computation of exact Zernike moments using cascaded digital filters
Information Sciences: an International Journal
Contact-free hand geometry-based identification system
Expert Systems with Applications: An International Journal
Hand shape recognition based on coherent distance shape contexts
Pattern Recognition
The location method of the main hand-shape feature points
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Hand shape recognition using Hu and Legendre moments
Proceedings of the 6th International Conference on Security of Information and Networks
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Hand-based verification is a key biometric technology with a wide range of potential applications both in industry and government. The focus of this work is on improving the efficiency, accuracy, and robustness of hand-based verification. In particular, we propose using high-order Zernike moments to represent hand geometry, avoiding the more difficult and prone to errors process of hand-landmark extraction (e.g., finding finger joints). The proposed system operates on 2D hand silhouette images acquired by placing the hand on a planar lighting table without any guidance pegs, increasing the ease of use compared to conventional systems. Zernike moments are powerful translation, rotation, and scale invariant shape descriptors. To deal with several practical issues related to the computation of highorder Zernike moments including computational cost and lack of accuracy due to numerical errors, we have employed an efficient algorithm that uses arbitrary precision arithmetic, a look-up table, and avoids recomputing the same terms multiple times [2]. The proposed hand-based authentication system has been tested on a database of 40 subjects illustrating promising results. Qualitative comparisons with state of the art systems illustrate comparable of better performance.