Combining fuzzy ART network clustering and sparse code shrinkage for image segmentation

An autonomous segmentation process is one of the most difficult tasks of a visual system. Among the main aspects that can affect the results of this process is the presence of noise. In this paper, it is showed how a technique for denoising images can be combined with the Fuzzy ART clustering for improving the image segmentation results. A mobile robot application is used for testing the efficiency of the proposed combination.