An heuristic cloud based segmentation technique using edge and texture based two dimensional entropy

The Edge detection will localize the objects and their boundaries within an image which is a basis for various image analysis and the applications of machine vision. There are conventional approaches to edge detection which are expensive in terms of computation as each set of such operations are conducted for every pixel. In case of approaches that are conventional the time taken for computation will increase with that of the image size. The edge detection is used extensively in case of image segmentation of the medical images. An Ant Colony Optimization algorithm consists of many advantages such as parallelism, robustness and easy computation.The Glowworm Swarm Optimization (GSO) is that probabilistic technique which is used for finding the optimal paths that are connected completely in the guided search by means of using the information on brightness. The technique is also used for solving problems in computation that are reduced in finding. In case of the GSO algorithm where the insects move in a search space that is dictated probabilistically by using transition probabilities. In this work, a heuristic cloud based segmentation is performed using edge method and texture based 2-Dimensional entropy. The results have shown that this method proposed has achieved better performance.

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