LIVENESS PALMPRINT DETECTION AND HUMAN RECOGNITION USING LOCAL MICRO-STRUCTURE TETRA PATTERN
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This paper proposes an approach for touchless detection of live palmprint and human recognition/identification. The method was implemented on Raspeberry Pi 4. The input palm print images are acquired by camera, from that the palm print areas are detected and extracted. Then, the region of interest in the palm print images are fed to a live palm print detection that is based on the changes of average image intensity in the image series according to blood flow changes in a circulation. After the object has detected as a live palm print case, the images are then applied to the human recognition/identification using Local Micro-structure Tetra Pattern. The experiments The proposed approach was applied on our acquired database including 15 subjects. The accuracy was up to 89% for live palm print detection, and 91% for human recognition/identification.
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