Optimal Thinning Algorithm for detection of FCD in MRI Images

Thinning is essentially a “pre-processing” step in many applications of digital image processing, computer vision, and pattern recognition. In many computer vision applications, the images interested in a scene can be characterized by structures composed of line or curve or arc patterns for shape analysis. It is used to compress the input data and expedite the extraction of image features. In this paper three different thinning algorithms are applied for MRI Brain Images to estimate performance evaluation metrics of thinned images. Image thinning reduces a large amount of memory usage for structural information storage. Experimental result shows the performance of the proposed algorithm.