快速二维最小交叉Tsallis熵的图像阈值分割

Fast Image Segmentation Based on 2-D Minimum Cross Tsallis Entropy

中文关键词:  图像分割  二维最小交叉熵  Tsallis熵  递推算法

英文关键词:image segmentation  2-D minimum cross entropy  Tsallis entropy  recursive algorithm

中文摘要:

      目前二维最小交叉Tsallis熵阈值分割法有较好的分割性能，但由于计算复杂度高，使得分割速度慢。针对此问题，提出了一种基于二维最小交叉Tsallis熵的快速图像分割方法。首先对二维最小交叉Tsallis熵法公式进行推导找出需要递推的几个量，然后对二维直方图投影进行分析得到二维直方图的特性；最后利用此特性导出新型的快速递推算法来减少计算时间。实验结果表明：相对于当前二维最小交叉Tsallis熵阈值法，提出的方法在保持分割效果的情况下，其速度提高了20倍以上，其运行时间小于0.2 s。

英文摘要:

      The current thresholding method based on 2-D minimum cross Tsallis entropy has good segmentation performance,but owing to high complexity its speed is so slow.So a fast image thresholding method based on 2-D minimum cross Tsallis entropy is presented.Firstly,the formula of 2-D minimum cross Tsallis entropy is deduced to find some variables to be recurred.Then,a two-dimensional histogram is analyzed to get its features.Finally,a new recursive approach is inferred with the features to reduce the computational complexity.Experimental results show that the proposed method’s computing time is less than 0.2 second and that its running speed is over 20 times faster,with the same segmentation result,than that of the current thresholding method based on 2-D minimum cross Tsallis entropy.