| 基于小波变异本质粒子群和模糊熵的图像分割 |
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| 引用本文： | 张伟.基于小波变异本质粒子群和模糊熵的图像分割[J].光电子．激光,2010(8):1264-1268. |
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| 作者姓名： | 张伟 |
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| 作者单位： | 山东大学控制科学与工程学院； 青岛科技大学自动化与电子工程学院； |
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| 基金项目： | 山东省自然科学基金资助项目(Z2006G06) |
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| 摘 要： | 针对本质粒子群(BBPSO)算法存在易陷入局部最优以及过早收敛的缺点,提出了一种基于小波变异(WM)BBPSO(WMBBPSO)和模糊熵的图像分割算法,利用WMBBPSO搜索使图像模糊熵最大的参数值,得到模糊参数的最优组合,进而确定图像的分割阈值。通过与其它两种BBPSO算法的分割结果比较表明,该算法取得了令人满意的分割结果,算法运算时间较小,能够满足对煤尘浓度实时精确测量的要求。
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| 关 键 词： | 本质粒子群(BBPSO) 小波变异(WM) 模糊熵 图像分割 阈值分割 |
Image segmentation based on wavelet mutation bare bones particle swarm optimization and fuzzy entropy |
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| ZHANG Wei.Image segmentation based on wavelet mutation bare bones particle swarm optimization and fuzzy entropy[J].Journal of Optoelectronics·laser,2010(8):1264-1268. |
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| Authors: | ZHANG Wei |
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| Affiliation: | School of Control Science and Engineering,Shandong University,Jinan 250061,China; School of Automation and Electronic Engineering,Qingdao University of Science and Technology,Qingdao 266042,China |
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| Abstract: | Bare bones particle swarm optimization(BBPSO) can not get good optimization performance because it is easy to get stuck into local optimum.Using wavelet mutation when no fitness improvement is observed,a new segmentation algorithm based on wavelet mutation BBPSO(WMBBPSO) and fuzzy entropy is proposed.The proposed algorithm uses WMBBPSO to explore fuzzy parameters of maximum fuzzy entropy,and the optimal fuzzy parameter combination is got,then the segmentation threshold is obtained.The experiment... |
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| Keywords: | bare bones particle swarm optimization(BBPSO) wavelet mutation(WM) fuzzy entropy image segmentation threshold segmentation |
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