TY - JOUR A2 - Liu, Yi-Hung AU - Charansiriphaisan, Kanjana AU - Chiewchanwattana, Sirapat AU - Sunat, Khamron PY - 2014 DA - 2014/03/20 TI - A Global Multilevel Thresholding Using Differential Evolution Approach SP - 974024 VL - 2014 AB - Otsu’s function measures the properness of threshold values in multilevel image thresholding. Optimal threshold values are necessary for some applications and a global search algorithm is required. Differential evolution (DE) is an algorithm that has been used successfully for solving this problem. Because the difficulty of a problem grows exponentially when the number of thresholds increases, the ordinary DE fails when the number of thresholds is greater than 12. An improved DE, using a new mutation strategy, is proposed to overcome this problem. Experiments were conducted on 20 real images and the number of thresholds varied from 2 to 16. Existing global optimization algorithms were compared with the proposed algorithms, that is, DE, rank-DE, artificial bee colony (ABC), particle swarm optimization (PSO), DPSO, and FODPSO. The experimental results show that the proposed algorithm not only achieves a more successful rate but also yields a lower threshold value distortion than its competitors in the search for optimal threshold values, especially when the number of thresholds is large. SN - 1024-123X UR - https://doi.org/10.1155/2014/974024 DO - 10.1155/2014/974024 JF - Mathematical Problems in Engineering PB - Hindawi Publishing Corporation KW - ER -