Adaptive hand image function region segmentation for intelligent aided diagnosis Online publication date: Fri, 05-Apr-2024
by Yang Liu; Jing Jie; Hui Zheng; Beiping Hou; Zhenglin Li
International Journal of Computing Science and Mathematics (IJCSM), Vol. 19, No. 3, 2024
Abstract: Smart hand diagnosis simulates the expert knowledge of hand diagnosis in traditional Chinese medicine and makes a diagnosis through the hand image information. To ensure the correctness of the diagnosis, an adaptive hand image function region segmentation is developed. Firstly, a hand image is acquired by a mobile app and its contour is extracted by multi-threshold segmentation and edge detection after series preprocessing. Secondly, some key feature corner points in the hand contour are detected through the dynamic intersection method, and then the hand image is segmented into 14 function regions, referring to the nine palace figures of hand diagnosis, in which the feature of each region can indicate the sampled people's health status for a specific physical function. The experimental results show that the hand image function regions can be divided successfully and keep the pathological characteristics in good condition. All that prove the segmentation method has good robustness and high accuracy.
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