The Otsu algorithm is one of the most widely applied threshold-based image segmentation algorithms. However, its rather large calculation amount and poor real-time quality has limited its further application. In this paper, a new segmentation method combined Otsu and particle swarm optimization is proposed. An improved particle swarm optimization with the improvements of particle's best fitness value as the inertia weight of PSO is proposed to improve the selecting speed of the threshold of Otsu. The experimental results demonstrated that the proposed method is better than the original Otsu and Otsu based on standard PSO in terms of both execution time and solution precision.
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