Entropic Image Segmentation: A Fuzzy Approach Based on Tsallis Entropy

ISSN: 2186-1390 http://www.ijcvsp.com Abstract In this paper, a fuzzy approach for image segmentation based on Tsallis entropy is introduced. This approach employs fuzzy Tsallis entropy to measure the structural information of image and to locate the optimal threshold desired by segmentation. The proposed method draws upon the postulation that the optimal threshold concurs with maximum information content of the distribution. The contributions of the work are as follow: Initially, fuzzy Tsallis entropy as a measure of spatial structure of image is described. Then, an unsupervised entropic segmentation method based on fuzzy Tsallis entropy is developed. Although the proposed approach belongs to entropic segmentation approaches (i.e., such approaches are commonly applied to grayscale images), it is adapted to be viable for segmenting color images. Finally, substantial experiments are carried out on realistic images to validate the effectiveness, efficiency and robustness of the proposed method.