Palmprint Recognition Based on Local Texture Features.
Samo Ribarič, Markan Lopar · 2013
In this paper, we propose and evaluate palmprint recognition method based on local Haralick features. The Haralick features are extracted from overlapping 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 features per subimage in the ROI. A live biometric template and templates from database are matched in N matching modules. Based on fusion at the matchingscore 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. [email protected]