Finger vein recognition method

Abstract

The invention discloses a finger vein recognition method. The method comprises the following steps: S1, a finger image under near infrared light is acquired; S2, preprocessing and denoising are carried out on the acquired finger image, an OSTU threshold method is then adopted to carry out threshold processing or ROI positioning on the finger image, and a finger binary image is acquired; S3, whether rotational distortion interference happens to the finger binary image is judged, and if yes, correction transformation is carried out; S4, a local adaptive threshold is used for carrying out vein feature extraction on the finger binary image, and a vein binary image is acquired; S5, a matching distance between an inputted vein binary image and a registered vein binary image is calculated; and S6, a K nearest neighbor algorithm is used for calculating a recognition result. The method has a strong anti-inteference ability, particularly adverse circumstances such as rotational translation distortion of the image, and at the same time, a false rejection rate and a false accpetance rate can be reduced.

Description

technical field [0001] The invention belongs to the technical field of image processing and biological identification, and in particular relates to a finger vein identification method. Background technique [0002] Hemoglobin has a strong absorption of near-infrared light and other tissues and bones are not too sensitive to near-infrared light. Therefore, when near-infrared light penetrates the finger, there will be some shadows in the veins, and these shadows are the veins. The vein part is under the skin of the human body, it is difficult to be copied and forged, and the finger veins have distinct individual specificity. Therefore, finger vein recognition technology has become an important way of identity authentication. [0003] Finger vein recognition has important application value in identity authentication, entrance and exit management, security monitoring, e-commerce, e-government and other fields, and has become one of the important research areas in biometric reco...

AI Technical Summary

Problems solved by technology

[0004] Existing finger vein recognition products have some problems, for example, they are easily interfered by factors such as light and shadow, and there will be certain translation, rotation, distortion, etc. every time the vein is collected.

However, the existing finger vein recognition has certain requirements for the placement of the finger, and the recognition rate is low when the finger is rotated or translated.

At the same time, in the existing template matching algorithms, the matching parameters are mostly selected based on experience, resulting in poor robustness of the algorithm

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