research-article

Deformed Palmprint Matching Based on Stable Regions

Authors:

Qiushi ZhaoAuthors Info & Claims

IEEE Transactions on Image Processing, Volume 24, Issue 12

Pages 4978 - 4989

https://doi.org/10.1109/TIP.2015.2478386

Published: 01 December 2015 Publication History

Abstract

Palmprint recognition (PR) is an effective technology for personal recognition. A main problem, which deteriorates the performance of PR, is the deformations of palmprint images. This problem becomes more severe on contactless occasions, in which images are acquired without any guiding mechanisms, and hence critically limits the applications of PR. To solve the deformation problems, in this paper, a model for non-linearly deformed palmprint matching is derived by approximating non-linear deformed palmprint images with piecewise-linear deformed stable regions. Based on this model, a novel approach for deformed palmprint matching, named key point-based block growing (KPBG), is proposed. In KPBG, an iterative M-estimator sample consensus algorithm based on scale invariant feature transform features is devised to compute piecewise-linear transformations to approximate the non-linear deformations of palmprints, and then, the stable regions complying with the linear transformations are decided using a block growing algorithm. Palmprint feature extraction and matching are performed over these stable regions to compute matching scores for decision. Experiments on several public palmprint databases show that the proposed models and the KPBG approach can effectively solve the deformation problem in palmprint verification and outperform the state-of-the-art methods.

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Cited By

Jia WGao JXia WZhao YMin HLu J(2020)A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein RecognitionInternational Journal of Automation and Computing10.1007/s11633-020-1257-918:1(18-44)Online publication date: 29-Dec-2020
https://dl.acm.org/doi/10.1007/s11633-020-1257-9
Jia WZhang BLu JZhu YZhao YZuo WLing H(2017)Palmprint Recognition Based on Complete Direction RepresentationIEEE Transactions on Image Processing10.1109/TIP.2017.270542426:9(4483-4498)Online publication date: 11-Jul-2017
https://dl.acm.org/doi/10.1109/TIP.2017.2705424

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Deformed Palmprint Matching Based on Stable Regions

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cover image IEEE Transactions on Image Processing

IEEE Transactions on Image Processing Volume 24, Issue 12

Dec. 2015

1399 pages

ISSN:1057-7149

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Copyright © 2015.

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IEEE Press

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Published: 01 December 2015

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Cited By

Jia WGao JXia WZhao YMin HLu J(2020)A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein RecognitionInternational Journal of Automation and Computing10.1007/s11633-020-1257-918:1(18-44)Online publication date: 29-Dec-2020
https://dl.acm.org/doi/10.1007/s11633-020-1257-9
Jia WZhang BLu JZhu YZhao YZuo WLing H(2017)Palmprint Recognition Based on Complete Direction RepresentationIEEE Transactions on Image Processing10.1109/TIP.2017.270542426:9(4483-4498)Online publication date: 11-Jul-2017
https://dl.acm.org/doi/10.1109/TIP.2017.2705424

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