Abstract
The present study deals with the image segmentation of waste wood material using some popular nature inspired metaheuristics like: Differential Evolution (DE), Particle Swarm Optimization(PSO) Artificial bee Colony (ABC) and Cuckoo Search (CS). Otsu’s between class-variance and Kapur’s maximum entropy techniques are used as fitness functions. Experiments have been performed on various images and numerical results are compared. It is observed that in some cases Otsu method is giving the same performance as DE, PSO, ABC and CS. But when class size increases DE shows better results in comparison to others.