Abstract

This paper presents two novel approaches for palmprint verification by scene match- ing. In a sense, the process of palmprint verification can be regarded as matching one palmprint template with another palmprint sample taken under conditions of different illumination, sensor pose geometry, or types of sensor, and making a decision of whether they belong to the same person or not. Enlightened by the idea of scene matching algorithms, two efficient approaches by scene matching are presented for palmprint verification. A sub-image from the user’s training palmprint is intentionally extracted, and stored as a template. In the verification stage, the sample image is directly matched with the template without the step of ROI (Region of Interest) extraction. Whether the sample image and the template are from the same person or not is decided by their matching scores. Experimental evaluation results on two databases clearly demonstrate the effectiveness of the proposed approaches.

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