Grey Scale Image Multi-Thresholding Using Moth-Flame Algorithm and Tsallis Entropy

In the current era, image evaluations play a foremost role in variety of domains, where processing digital images is essential to identify vital information. The multi-thresholding pre-processing field which available enhanced by grouping similar pixel values. Normally, test are RGB/greyscale format and appropriate methodology treat with chosen methodology. proposed approach, Tsallis Entropy (TE) supported multi-level thresholding planned for benchmark greyscale imagery dimension 512x512x1 pixels using threshold values (T=2,3,4,5). This work suggests possible Cost Value (CV) that can be considered during optimization search executed considering maximization TE as CV. entire task Moth-Flame Algorithm (MFA) accomplished results validated based on quality measures various thresholds. attained result MFO better compared CS, BFO, PSO, GA.