摘要
针对三维Otsu分割算法运算量大的问题,本文提出了一种基于最佳熵的三维Otsu图像分割算法。文章中,我们首先采用最佳熵方法初步提取图像的目标区域,并根据目标区域的平均灰度确定三维Otsu图像分割算法的背景区域搜索范围,然后采用三维Otsu算法并结合遗传算法对原图像进行分割。实验结果表明,与三维Otsu阈值分割方法的递推算法相比,该方法能够进一步减少运算时间。
Aiming at the weakness of the huge calculation of the three-dimension Otsu, a method for image segmentation of three-dimension Otsu based on optimal entropy is presented in this paper. Firstly, the target region are segmented through optimal entropy method. Then based on the mean gray value of the target region specify the background area ranges. Finally the target image is obtained via the three-dimensionOtsu and genetic algorithm. Comparing with the image segmentation based on 3-D maximum between cluster variance, the simulation results show that the performance of this method is superior in operation time.
出处
《电气电子教学学报》
2010年第4期51-54,共4页
Journal of Electrical and Electronic Education
基金
湖南省教育厅项目(06C517)
关键词
图像分割
三维Otsu
遗传算法
最佳熵
image segmentation
three-dimension Otsu genetic algorithm optimal entropy
