Grey and Color Image Segmentation by Reptile Search Algorithm aided with Tsallis entropy

Image segmentation provides immense information from the image for real life applications. In this paper, multilevel thresholding based Tsallis fitness function is used for image segmentation. The goal to reach the optimal threshold is gained through effective robust hunting and encircling approaches of Reptile Search Algorithm (RSA). The streamlined body structure of crocodiles enables quick movement, pattern recognition through advanced skills and coordination, collaboration as a team hunt the prey drives the way for precise segmented images. Well balanced exploration and exploitation promotes the way for accurate and precise image segmentation. The proposed method using RSA based Tsallis entropy objective function is applied and tested with $t=2,3,4,5$ threshold levels for grey images and the color images with 4,5,6 and 7 threshold levels. Validation is attained through the metric Peak Signal to Noise Ratio (PSNR) comparing with the Krill herd Algorithm (KHA) and Cuckoo Search Algorithm (CSA).