李晓玲, 吴慧丽, 鹿艳晶, 李凯. 基于智能Fisher和灰色后处理的图像分割方法[J]. 微电子学与计算机, 2012, 29(11): 82-86.
引用本文: 李晓玲, 吴慧丽, 鹿艳晶, 李凯. 基于智能Fisher和灰色后处理的图像分割方法[J]. 微电子学与计算机, 2012, 29(11): 82-86.
LI Xiao-ling, WU Hui-li, LU Yan-jing, LI Kai. Image Segmentation Method Based on Intelligence Fisher Criterion and Grey Post Processing[J]. Microelectronics & Computer, 2012, 29(11): 82-86.
Citation: LI Xiao-ling, WU Hui-li, LU Yan-jing, LI Kai. Image Segmentation Method Based on Intelligence Fisher Criterion and Grey Post Processing[J]. Microelectronics & Computer, 2012, 29(11): 82-86.

基于智能Fisher和灰色后处理的图像分割方法

Image Segmentation Method Based on Intelligence Fisher Criterion and Grey Post Processing

  • 摘要: 针对图像分割中最佳阈值选取及运算速度问题,本文提出Fisher准则和灰色关联分析有效结合的方法来给予解决.该方法首先引入模式识别理论中的Fisher判别准则,针对遍历目标函数速度慢的问题,结合PSO算法对其进行快速的优化处理,提高了工作效率,更快地逼近最佳阈值;最后根据图像的特点,采取灰色关联分析,对已经分割的图像进行再次处理,可以消除边界区域的信息对最终分割结果的不利影响,由此得到更为准确、精细的分割图像.

     

    Abstract: Aiming at the threshold selectiong and slow speed in image segmentation, the paper suggests a effective method based on Fisher criterion and grey correlation analysis.In the method, a 2D entropy model is designed to locate the best threshold value via Fisher criterion.Additionally, Particle Swarm Optimization (PSO) is introduced to speed up the segmentation procedure.Finally, the segmented image was processed by grey correlation analysis according to image's character.Some exeperimental results indicate that the new algorithm ignores the disturbance of inherent speckle in image and get accurate image segmentation.

     

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