Image Segmentation Based On Fruit Flies Optimization Fuzzy Kernel Clustering In The NSCT Domain

Image segmentation plays an important role in digital image processing, quality of image segmentation will directly affect the follow-up work can accurate smoothly. Owing to many uncertainties exist in the imaging process, causing to extract certain similarity between target and background and uncertainty, based on the theory of fuzzy image processing technology can effectively improve the problem of uncertainty, and KFCM algorithm of image feature has very good adaptability, good robustness to noise suppression, so this article uses the KFCM algorithm for image segmentation.Since the KFCM algorithm is sensitive to the initial value, easy to converge to local extremum problem, The flies algorithm can be carried out on the global optimization,so this article puts forward the KFCM algorithm for parameters optimization based on fruit flies, So that the algorithm can better converge to global optimal solution, But based on fruit flies optimization KFCM algorithm for image segmentation and edge information is incomplete,the less texture information, so this article on the basis of optimization KFCM algorithm based on fruit flies, NSCT transform is introduced.Image after NSCT transform can more effectively capture images of geometry information, So this article puts forward the NSCT domain KFCM image segmentation algorithm based on fruit flies optimization. For different types of image segmentation experiments, the results show that the NSCT domain KFCM image segmentation algorithm based on fruit flies optimization is applied to the type of image segmentation, and can get more detail information, and the edge is more apparent, achieved the good segmentation effect.