A Fuzzy Adaptive Firefly Algorithm for Multilevel Color Image Thresholding Based on Fuzzy Entropy

Multilevel thresholding image segmentation has been a hot issue of research in the last several years since it has a plenty of applications. The meta-heuristic search algorithm has unique advantages in solving multilevel threshold values. In this paper, a fuzzy adaptive firefly algorithm (FaFA) is proposed to solve the optimal multilevel thresholding for color images, and the fuzzy Kapur’s entropy is considered as its objective function. In the FaFA, a fuzzy logical controller is designed to adjust the control parameters. A total of six satellite remote sensing color images are conducted in the experiments. The performance of the FaFA is compared with FA, BWO, SSA, NaFA, and ODFA. Some measure metrics are performed in the experiments. The experimental results show that the FaFA obviously outperforms other five algorithms.