engleski

Palmprint Recognition Based on Local Texture Features

In this paper, we propose and evaluate palmprint recognition method based on local Haralick features. The Haralick features are extracted from over-lapping square subimages of a palmprint region of interest (ROI). A biometric template is composed of N m-component feature vectors, where N is the total number of overlapping subimages, and m is the number of local Haralick fea-tures per subimage in the ROI. A live biometric template and templates from database are matched in N matching modules. Based on fusion at the matching-score level, the total similarity measures between a live biometric template and templates from the database are calculated. By using the maximum of total similarity measure and the 1-NN classification rule, the final decision (person identity) is made. The proposed palmprint recognition system was tested on the PolyU database. The results of open set identification are given.

Palmprint recognition; local Haralick features; Open set identification

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