Abstract: The project presents robust palm vein recognition using hybrid texture descriptors like discriminative robust local ternary pattern and Weber’s local descriptor for improving the recognition accuracy. A Biometric system is actually a pattern recognition system that makes use of biometric traits to recognize individuals. There was a negative effect on recognition performance on fingerprint and palm print biometrics thanks to the some conditions such as oil on the fingers, moisture, and dirt. Therefore, vein patterns stand out from the host of intrinsic biometric traits for development of a recognition system which will meet all these expectations. Vein patterns are the network structure of blood vessels underneath the human skin that are almost invisible to the eye under natural lighting conditions and can be acquired in infrared illumination, which effectively protects against possible external damage, spoof attacks and impersonation. The feel of the blood vessels of different individuals has been proven to be distinctive even among identical twins. Initially the palm vein images are pre-processed to pick the region of interest for vein pattern extraction. Here, local thresholding is employed to extract the vein pattern for its texture analysis. Two textures descriptors called Weber’s local descriptors and DRLTP (Discriminative Robust Local Ternary Pattern) are proposed to extract the features about texture for recognizing with original templates. DRLTP is employed to provide the shape and contrast invariant features of an object. WLD provides details about illumination changes between the pixels. Euclidean distances are going to be used to match the features of test and original templates for making decision on person biometric. Finally the performances of proposed algorithm are going to be measured with recognition accuracy and it proves that it provides better matching rate than prior approaches.

Keywords: Palm vein, Biometric, Weber local descriptors, DRLTP, Euclidean distance.

PDF | DOI: 10.17148/IJARCCE.2022.11777

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