摘要
为了克服二维Shannon熵阈值法的缺陷,提出了一种使用矩不变法来调整二维直方图斜分Shannon熵的阈值分割方法。首先将二维直方图斜分原理运用到两种Shannon熵阈值法中,然后利用矩不变法从两种熵阈值法获取的阈值中选择最佳阈值,并提出二维直方图斜分Shannon熵阈值法的一般递推算法,最后将二维直方图分布特性与这种算法有机结合得到新型快速的递推算法。实验结果表明,提出的方法不仅分割效果优于当前的二维直方图斜分的最大熵阈值法,而且运行速度更快,约快4倍。
In order to overcome the drawbacks of the 2-D Shannon entropy image thresholding method,a preserving-moment-modified Shannon entropy image thresholding method based on 2-D histogram oblique segmentation was pre-sented.First the two thresholding methods based on Shannon entropy were formulated by the oblique line which is perpendicular to the main diagonal;then the optimal threshold was chosen from the thresholds obtained from these methods using the preserving-moment principle,and its recursive algorithm of the method based on 2-D histogram oblique segmentation was inferred,finally the features of 2-D histogram and the algorithm were combined to get a novel recursive algorithm.Experimental results show that the proposed method＇s segmentation performance is much better and its running speed is about four times faster,compared with the current maximum entropy method based on 2-D oblique segmentation.
出处
《计算机科学》
CSCD
北大核心
2012年第1期276-280,共5页
Computer Science
基金
国家自然科学基金项目(60873104)
河南省重点科技攻关项目(102102210180)资助
关键词
图像分割
阈值化
二维直方图斜分
矩不变法
Shannon熵
Image segmentation
Thresholding
2-D histogram oblique segmentation
Moment-preserving principle
Shannon entropy
