On acquisition and classification for thenar palmprint image

In order to get clear thenar palmprint image, we design a thenar palmprint collection and processing system. According to the optical lighting technology, we stabilize the lighting condition with ring light to highlight the feature of thenar palmprint. Using industrial digital camera and fixed lens to highlight anti-jamming capability and get the stable image. Secondly, Grey Level Co-occurrence Matrix method was adopted to extract the image features which can be used in binary classification. Finally, the recognition of the two categories of thenar palmprint is achieved based on Support Vector Machine. Simulation results show that the image processing and recognition algorithms designed in this paper has a high efficiency and accuracy to the negative and positive classification.