Finger vein image quality evaluation method based on image processing

Abstract

The invention discloses a finger vein image quality evaluation method based on image processing. The method comprises the following steps: 1) acquiring an originally acquired finger vein region-of-interest picture; 2) filtering image noise by using mean filtering and median filtering to obtain a denoised image; 3) enhancing the contrast of the denoised image by using homomorphic filtering to obtain a contrast-enhanced image; 4) enhancing texture details of the contrast-enhanced image by using directional texture filtering to obtain a texture-enhanced image; 5) setting a threshold value, and performing binarization processing on the image after the texture enhancement to obtain a finger vein binary image; and 6) performing connected domain analysis on the finger vein binary image by using the connected domain information, removing a region with the area smaller than a threshold value, and counting the area of the remaining region to obtain an image quality score. The method can effectively reflect the quality of the collected finger vein image, thereby effectively solving the problem of no universal finger vein image quality evaluation method.

Description

technical field [0001] The invention relates to the technical field of finger vein biometrics, in particular to a method for evaluating the quality of finger vein images based on image processing. Background technique [0002] Finger vein recognition is a biometric technology for identification based on human finger vein feature information. The feature of finger vein recognition comes from the hemoglobin in the blood flowing in the finger veins, which is stealthy and alive. The image of the finger vein is obtained through a device based on near-infrared light collection, and the vein area is reflected in the darker lines on the image. That is, the venous blood vessel area collected by the device. However, it is limited by the quality of the acquisition equipment and environmental factors such as background light and ambient temperature, which cause finger capillary constriction to affect the image. The quality of the collected finger vein images is uneven, and under harsh...

AI Technical Summary

Problems solved by technology

However, the existing image quality evaluation algorithms, such as the spatial domain image quality evaluation algorithm without reference image (BRISQUE), are used to evaluate the quality of image distortion. For finger vein images, the clarity of the lines is the key to the quality of finger vein images. Subjective evaluation indicators, so the commonly used general image quality evaluation algorithm is not robust enough for finger vein image quality evaluation, and it is not targeted

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