An Efficient Finger Vein Image Enhancement and Pattern Extraction Using CLAHE and Repeated Line Tracking Algorithm

Abstract

Finger vein recognition is documented as one of the effectual biometric technique today for person identification because of its following advantages: Contactless sensor, low cost, living body authentication and complex security. Pattern extraction is an essential process that is used to extract the cleared specific vein patterns from the spurious finger vein image. In this paper, the repeated line tracking algorithm is endeavored to extort the vein samples adequately. In order to attain the improved extraction consequence, the image is enhanced by using Contrast Limited Adaptive Histogram Equalization (CLAHE) before employing the extraction progress. For this purpose we are taking a publicly available dataset namely UTFVP. Subsequently a performance comparison is given for our proposed work in the aspect of some quality measures as PSNR, MSE and SSIM values for before and after processing. Experimental result shows that the simplicity, reliability and sturdiness of the proposed pattern extraction method.