Gray Scale Image Multi-Thresholding with Chaotic Cuckoo Search

Image processing field is widely adopted in a variety of domains to examine and extract the vital features. Image multi-thresholding is an essential pre-processing field, widely implemented to pre-process the classical and medical images. In this paper, pre-processing of benchmark gray scale is implemented using the Chaotic Cuckoo Search (CCS) algorithm using the Tsallis entropy value. The experimental investigation is implemented with the Matlab7 software using test images of 512x512 pixels. The performance of CCS is confirmed with the other heuristic methods, such as FA, BA and PSO. The experimental results of this study verify that, implemented CCS tenders enhanced outcome with improved image quality measures and the run time compared with other algorithms adopted in this paper. This work confirms that, chaotic algorithms are better than the conventional approaches.