Finger vein image quick segmentation method based on active contour model

Abstract

The invention belongs to the field of image processing, provides a method for quickly segmenting a finger vein image, and provides reliability guarantee for subsequent feature extraction and recognition of finger veins. Therefore, the technical scheme adopted by the invention is as follows. The invention discloses a finger vein image quick segmentation method based on an active contour model. A fuzzy kernel clustering KFCM algorithm is used to preliminarily determine a general contour of a vein area. And establishing a target functional, taking the preliminarily determined general contour of the vein region as an initial contour of the established target functional optimization, continuously iteratively solving a minimum value of the target functional, and continuously evolving the initialcontour in an iterative optimization process until an optimal segmentation result is achieved, thereby finally realizing image segmentation. The method is mainly applied to image processing occasions.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a finger vein image segmentation method. Specifically, a fast finger vein segmentation method involving an active contour model. Background technique [0002] As a new biometric method, finger vein recognition technology has more unique advantages compared with traditional biometric technologies such as fingerprint recognition, palmprint recognition, and face recognition: (1) non-contact; (2) living body detection; (3) high security; (4) portability. Therefore, finger vein recognition technology has wider development space and application prospects. [0003] The key to finger vein recognition technology is to effectively segment vein image information that can represent identity characteristics from finger vein images, and whether the vein information can be accurately segmented will directly affect the final identification accuracy. Since most finger vein collection devices us...

AI Technical Summary

Problems solved by technology

[0004] 1. Affected by uneven illumination, the quality of the collected finger vein images is not high, the contrast is poor, and it is difficult to distinguish the vein area from the background area;

[0005] 2. Affected by different finger postures, shadow areas are easy to appear in finger vein images, which increases the difficulty of vein region segmentation to some extent

More importantly, such methods may cause changes that alter the original vein structure

Images