Enhancement of Finger-Vein Image by Vein Line Tracking and Adaptive Gabor Filtering for Finger-Vein Recognition

Abstract

Biometrics is the technology to identify a user by using the physiological or behavioral characteristics. Among the biometrics such as fingerprint, face, iris, and speaker recognition, finger-vein recognition has been widely used in various applications such as door access control, financial security, and user authentication of personal computer, due to its advantages such as small sized and low cost device, and difficulty of making fake vein image. Generally, a finger-vein system uses near-infrared (NIR) light illuminator and camera to acquire finger-vein images. However, it is difficult to obtain distinctive and clear finger-vein image due to skin scattering of illumination since the finger-vein exists inside of a finger. To solve these problems, we propose a new method of enhancing the quality of finger-vein image. This research is novel in the following three ways compared to previous works. First, the finger-vein lines of an input image are discriminated from the skin area by using local binarization, morphological operation, thinning and line tracing. Second, the direction of vein line is estimated based on the discriminated finger-vein line. And the thickness of finger-vein in an image is also estimated by considering both the discriminated finger-vein line and the corresponding position of finger-vein region in an original image. Third, the distinctiveness of finger-vein region in the original image is enhanced by applying an adaptive Gabor filter optimized to the measured direction and thickness of finger-vein area. Experimental results showed that the distinctiveness and consequent quality of finger-vein image are enhanced compared to that without the proposed method.

A Systematic Review of Finger Vein Recognition Techniques

“…However, in conventional approaches handcrafted descriptors (Curvature, Gabor filter, Radon transform, Information capacity, etc.) are employed to extract features from finger vein images [49,52,135]. In addition, introducing deep learning to finger vein recognition can reduce the total processing time of recognition.…”

Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors

“…The restoration-based methods proposed by Yang et al [ 9 , 10 , 11 ] were able to produce enhanced finger-vein images by considering the effect of the layered structure of skin and restored the images by using a point-spread function (PSF) model [ 10 ], and a biological optical model (BOM) [ 11 ]. In the non-restoration-based approaches, Gabor filtering was popularly used [ 6 , 7 , 8 , 12 , 13 ]. Yang et al introduced an enhancement method that uses multi-channel even-symmetric Gabor filters with four directions to strengthen the vein information in different orientations [ 6 ].…”

“…A study by Park et al [ 8 ] led to the proposal of an image enhancement method using an optimal Gabor filter based on the directions and thickness of the vein line. An adaptive version of the Gabor filter was used in the research of Cho et al [ 12 ] to enhance the distinctiveness of the finger-vein region in the original image. The Gabor filter was also used in combination with a Retinex filter, by using fuzzy rules in the method proposed by Shin et al [ 7 ].…”

A Novel Approach for Finger Vein Pattern Enhancement using Gabor and Canny Edge Detector

“…Miural et all in 2011 [13] used repeated line racking to tract the local dark position of image but it was difficult to define a shape for variable width veins. While Cho et al in 2011 [14] used an adaptive version of Gabor filter to enhance the distinctiveness region in the original finger vein image. Yang et al [10] produced enhanced finger vein image by restoration-based method through consideration n effect of the layered structured of skin.…”