Hybrid Swarms Optimization Based Image Segmentation

This chapter proposed multilevel thresholding hybrid swarms optimization algorithm for image segmentation. The proposed algorithm is inspired by the behavior of fireflies and real spider. It uses Firefly Algorithm (FA) and Social Spider Optimization (SSO) algorithm (FASSO). The objective function used for achieving multilevel thresholding is the maximum between class variance criterion. The proposed algorithm uses the FA to optimize threshold, and then uses this thresholding value to partition the images through SSO algorithm of a powerful global search capability. Experimental results demonstrate the effectiveness of the FASSO algorithm of image segmentation and provide faster convergence with relatively lower CPU time.

https://link.springer.com/chapter/10.1007/978-3-319-47223-2_1