Novel Image Quality Assessment and Enhancement Techniques for Finger Vein Recognition
Kashif Shaheed, Lu Yang, Gongping Yang, Imran M. Qureshi, Yilong Yin · 2018
As a secure and reliable biometric trait, finger vein recognition (FVR) can be employed to verify the individuals in real-time applications. However, the pattern of vein is unclear in some finger vein images due to light scattering by the skin and non-uniform illumination, which deteriorates the performance of the FVR system. To deal with the image quality problem, a novel finger-vein image quality assessment method and an enhancement method are proposed. The proposed FVR Scheme is based on two folds: (i) Image Quality Assessment, and (ii) Image Enhancement. First, the quality of the image is assessed by the decision tree with r-smote technique, to classify the finger vein image into two classes, i.e. High Quality (HQ) and Low Quality (LQ) images. Second, a single scale retinex filter (SSR) with chromaticity preserved algorithm and Gaussian filter are proposed to enhance the low and high quality finger vein images. Total of 1052 finger vein images are employed for the testing aspect of quality evaluation, enhancement and recognition method. After that, low error rate EER of 0.0379 is obtained by the proposed art. Finally, the achieved results show the strength of the proposed art is better than already developed methods in FVR domain.