Personal Identification Using Palmprint Biometrics Based on Principal Line Approach
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 7
Abstract
Palmprint is the one of the important biometrics characteristics with higher user acceptance. In palmprint, palm-lines are more important features for personal identification. In this paper, in preprocessing a Gaussian filter is used to smooth the image and next ROI is extracted based on valley points. The Canny edge detection operation is proposed to extract principal line features. The edge direction and gradient strength of each pixel in the preprocessed image are found using Sobel masks. Then edges are traced using that information. Finally, non-maximum edges are suppressed by finding parallel edges and eliminating those with weaker gradient strengths. In this way principal lines are extracted and resultant image is obtained. The matching is done by dividing the resultant image into 9X9blocks. The blocks are traced to create feature vector. While generating a template the feature vector bit is set if the concerned block contains the line. Personal identification is done based on the distance matching between the stored templates and the test palmprint image. Experiments show that the proposed method using PolyU palmprint database offer the accuracy of 86% personal identification
Authors and Affiliations
Sumangala Biradar
Keywords
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