改进的Otsu算法在图像分割中的应用

Application of an improved Otsu algorithm in image segmentation

针对二维Otsu自适应阈值算法计算复杂度高的问题,提出一种新的快速有效的Otsu图像分割改进算法。该算法通过求两个一维Otsu法的阈值来代替传统的二维Otsu法的分割阈值,使得分割的计算复杂度从O(L4)降到O(L)。为保证分割对象的完整性,算法引入类内最小离散度的概念,并通过遗传算法实现对参数的自动优化。理论分析和实验结果表明本算法计算速度不仅优于原二维Otsu算法,而且分割效果较好。

Considering the problem that the two-dimensional Otsu adaptive threshold algorithm is time-consuming,an improved two-dimensional Otsu threshold image segmentation algorithm is proposed.By calculating two 1D Otsu＇s threshold algorithm instead of the traditional 2D Otsu＇s threshold algorithm,the complexity of the algorithm is reduced from O（L4） to O（L）.In order to guarantee the integrity of the object,the minimum within-cluster scattered degree is added into the proposed algorithm,and the genetic algorithm is used to realize automatic optimizing the parameter.Theoretical analysis and experimental results show that this improved method is better than the traditional 2D Otsu not only in the computation time,but also in the quality.