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Issue No. 08 - Aug. (2012 vol. 34)
ISSN: 0162-8828
pp: 1618-1632
Jianjiang Feng , Dept. of Autom., Tsinghua Univ., Beijing, China
Jifeng Dai , Dept. of Autom., Tsinghua Univ., Beijing, China
Jie Zhou , Dept. of Autom., Tsinghua Univ., Beijing, China
During the past decade, many efforts have been made to use palmprints as a biometric modality. However, most of the existing palmprint recognition systems are based on encoding and matching creases, which are not as reliable as ridges. This affects the use of palmprints in large-scale person identification applications where the biometric modality needs to be distinctive as well as insensitive to changes in age and skin conditions. Recently, several ridge-based palmprint matching algorithms have been proposed to fill the gap. Major contributions of these systems include reliable orientation field estimation in the presence of creases and the use of multiple features in matching, while the matching algorithms adopted in these systems simply follow the matching algorithms for fingerprints. However, palmprints differ from fingerprints in several aspects: 1) Palmprints are much larger and thus contain a large number of minutiae, 2) palms are more deformable than fingertips, and 3) the quality and discrimination power of different regions in palmprints vary significantly. As a result, these matchers are unable to appropriately handle the distortion and noise, despite heavy computational cost. Motivated by the matching strategies of human palmprint experts, we developed a novel palmprint recognition system. The main contributions are as follows: 1) Statistics of major features in palmprints are quantitatively studied, 2) a segment-based matching and fusion algorithm is proposed to deal with the skin distortion and the varying discrimination power of different palmprint regions, and 3) to reduce the computational complexity, an orientation field-based registration algorithm is designed for registering the palmprints into the same coordinate system before matching and a cascade filter is built to reject the nonmated gallery palmprints in early stage. The proposed matcher is tested by matching 840 query palmprints against a gallery set of 13,736 palmprints. Experimental results show that the proposed matcher outperforms the existing matchers a lot both in matching accuracy and speed.
statistical analysis, image matching, image registration, image segmentation, palmprint recognition, sensor fusion, palmprints gallery, ridge-based palmprint matching, biometric modality, palmprint recognition system, large-scale person identification, orientation field estimation, statistical analysis, segment-based matching, fusion algorithm, skin distortion, orientation field-based registration algorithm, coordinate system, cascade filter, palmprint regions, computational complexity reduction, palmprints registration, Algorithm design and analysis, Feature extraction, Accuracy, Humans, Skin, Bones, Computational complexity, naive Bayes classifier., Palmprint, orientation field, density map, data fusion, distortion, matching, cascade filtering, generalized Hough transform

Jianjiang Feng, Jifeng Dai and Jie Zhou, "Robust and Efficient Ridge-Based Palmprint Matching," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 34, no. , pp. 1618-1632, 2012.
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