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Textural analysis of side-scan sonar images is performed by geologists to identify regions of the ocean floor. In this project, we are using AI techniques to classify regions in order to assist the geologists. The process divides the original image into rectangular regions called texels. From these texels, a set of features is mathematically calculated, and we cluster based on these features. The classified data is reconstructed into an image and we compare this image to the original image, using subjective criteria to gauge success. Evaluating success is often a subjective process that should involve domain experts. Two important decisions during the process are the size of the texels to consider and the combinations of features upon which to cluster.

Choosing the optimal features and texel sizes in image