Abstract: A new region growing algorithm for image segmentation is proposed，which is based on Particle Swarm Optimization algorithm by utilizing particle swarm’s power searching ability to search pixel seeds.Because searching pixel seeds are based on density and the computational load is small，the computing speed of the algorithm can be improved obviously.Compared to traditional RG method，the proposed algorithm can overcome the disadvantages that traditional RG method can’t select seeds automatically and leads to over-segment.The results indicate that the algorithm can segment the image accurately and precisely.

Key words: image segmentation, region growing, seed, particle swarm optimization algorithm

摘要： 提出了一种基于微粒群算法的区域生长图像分割方法，该方法利用微粒群较强的搜索能力搜索像素种子点。由于搜索像素种子点是按密度进行，计算量小，大幅度提高了算法的计算速度，同时克服了传统区域生长方法不能自动选择种子且容易导致过分割的局限性。实验表明，该方法可以准确地分割出目标，是一种有效的图像分割方法。

关键词: 图像分割, 区域生长, 种子, 微粒群优化算法