An Otsu thresholding for images based on a nature-inspired optimization algorithm

Thresholding is a type of image segmentation, where the pixels change to make easier analyze. In bi-level thresholding, in grayscale format transformed into binary format. The traditional methods for thresholding may be inefficient finding best threshold and take longer computation time. Recently, metaheuristic swarm-based algorithms were applied optimization different applications find optimal solutions with minimum computational proposed work aims optimize fitness function obtained by Otsu algorithm using called bat algorithm. As result, value images cloud detection was obtained. Also, one trajectory-based hill climbing taken from HYTA dataset used evaluate work, which later confirmed through testing. findings experiments indicated that developed promising performance population-based better than terms efficiency time thresholding.