Segmentation algorithm of digital dorsal joint pattern image based on morphological operation

When using the non-contact method to collect the image of the back of the hand, in view of the problems that the different degrees of finger opening and closing affect the segmentation of the finger image, the area of interest of the knuckles of the knuckles is difficult to locate, and the image is easily affected by light, a knuckles of the knuckles of the knuckles based on morphological operations are proposed. Region of interest positioning method. In this method, a combination of opening and closing operations in morphological operations is used to construct an image mask of the back of the hand, and then the mask is used to shield the area of the back of the hand, and five images of the back of the finger are separated and angle-corrected. For the corrected image, the top-hat transformation is performed first, and then the method of combining the sliding window algorithm with image information entropy is used to locate the knuckle pattern area of the dorsum of fingers. Finally, LBP and SIFT are used for feature extraction, and support vector machine (SVM) is used as a classifier, and experimental verification is carried out on the self-built back of hand image database. The experimental results show that the proposed method can eliminate the influence of illumination and environmental noise, and can accurately and quickly locate and extract the region of interest of the dorsal knuckle pattern on the back of the hand image.