Image multi-level-thresholding with Mayfly optimization

<span>Image thresholding is a well approved pre-processing methodology and enhancing the image information based on chosen threshold always preferred. This research implements mayfly optimization algorithm (MOA) multi-level-thresholding class of benchmark images dimension 512x512x1. The MOA novel with phases, such as; i) Initialization, ii) Exploration male-mayfly (MM), iii) female-mayfly (FM), iv) Offspring generation and, v) Termination. strict two-step search procedure, in which every Mayfly forced to attain global best solution. proposed considers value from 2 5 superiority result confirmed by computing essential Image quality measures (IQM). performance also compared validated against other procedures, as particle-swarm-optimization (PSO), bacterial foraging optimization</span><span>(BFO), </span><span lang="EN-IN">firefly-algorithm</span><span>(FA), bat (BA), cuckoo search</span><span>(CS) moth-flame (MFO) attained p-value Wilcoxon rank test algorithms considered this work</span>