Fuzzy clustering recognition algorithm of medical image with multi-resolution feature

Most current medical images are collected in the presence of interference by ignored interferences such as illumination, occlusion, etc. The recognition rate is low for multi-resolution images in the case of color distortion. Therefore, a novel fuzzy clustering recognition algorithm of multi-resolution medical image was proposed in this paper. First, medical images were analyzed from both acquisition time, shooting angle, resolution, natural light measurement, and background. Secondly, in order to avoid partial occlusion, region was recalculated by correlation between Fourier and Merlin transform. Moreover, Euclidean distance between samples were identified by standardized eigenvalues, where smallest distance obtained maximum degree of membership. Experiment results showed that the proposed method had higher recognition rate (accuracy 90.46% and sensitiveness 97.89%) and stronger anti-interference than current methods.