A fast and robust image segmentation method based on superpixels

Abstract

This paper proposes a novel fast and robust image segmentation method based on superpixels (FRISS). In order to make the algorithm adaptive as well as efficient, we first compute superpixels of the image with modified SLIC. Moreover, a modified SimHash is encoded for each superpixels. In addition, similar superpixels are associated together according to the similarity measure gotten from the Hamming distance of SimHash. FRISS can segment image with the given threshold of the similarity, which demonstrates its’ adaptation. On the other hand, the similarity is computed by the Hamming distance of SimHash code which is much faster than other similarities. From the experimental results, we can know that FRISS is fast and efficient.