Title :
A gray-level threshold selection method based on maximum entropy principle
Author :
Wong, Andrew K.C. ; Sahoo, P.K.
Author_Institution :
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Abstract :
A description is given of a gray-level threshold selection method for image segmentation that is based on the maximum entropy principle. The optimal threshold value is determined by maximizing the a posteriori entropy subject to certain inequality constraints which are derived by means of spectral measures characterizing uniformity and the shape of the regions in the image. For this purpose, the authors use both the gray-level distribution and the spatial information of an image. The effectiveness of the method is demonstrated by its performance on some real-world images. An extension of this method to chromatic images is provided
Keywords :
entropy; pattern recognition; a posteriori entropy; chromatic images; gray-level threshold selection method; image segmentation; maximum entropy principle; optimal threshold value; pattern recognition; Councils; Cybernetics; Design engineering; Entropy; Image segmentation; Mathematics; Permission; Pixel; Shape measurement; Systems engineering and theory;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
