Segmentation of blurred images using improved Chan-Vese snake model

Abstract

Accurately extracting the features of interest from a blurred image is one of the difficult tasks in image segmentation. This paper uses the blind deconvolution, deblurring algorithm to find original features of interest, and then uses the improved Chan -Vese snake model to get the accurate features. The presented algorithm is tested on the MRI images of brain and results are found to be satisfactorily.