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In this paper, we have developed Biometric recognition system adopting handbased modality Handvein, which has the unique pattern for each individual andit is impossible to counterfeit and fabricate as it is an internal feature. Wehave opted in choosing feature extraction algorithms such as LBP-visualdescriptor ,LPQ-blur insensitive texture operator, Log-Gabor-Texturedescriptor. We have chosen well known classifiers such as KNN and SVM forclassification. We have experimented and tabulated results of single algorithmrecognition rate for Handvein under different distance measures and kerneloptions. The feature level fusion is carried out which increased theperformance level.

Parametic Classification of Handvein Patterns Based on Texture Features