Otsu准则下分割阈值的快速计算

摘要

The traditional Otsu algorithm has to exhaustively compute all between-class variances. Based on one characteristic of Otsu threshold, this paperwork proposes a new fast algorithm.The new algorithm finds out every threshold which is equal to the integer part of the average of the mean levels of two classes, and then selects one threshold which is in accord with Otsu criterion. The traditional Otsu algorithm cannot work well when it extracts small object from gradient image, so an improved thresholding algorithm is proposed. Based on the fast Otsu algorithm provided, the improved thresholding algorithm recursively computes threshold. Experimental results show that the fast Otsu algorithm is faster than the traditional Otsu algorithm. Experimental results also show that the improved thresholding algorithm is effective to segment small object of gradient image.%传统Otsu法在确定阈值时需要穷举计算图像中每个灰度值为阈值时的类间方差.文中利用Otsu阈值的性质,提出了一个新算法以快速计算Otsu阈值.新算法搜寻出与两类类内均值的平均值的整数部分相等的阈值,从中确定一个符合Otsu准则的阈值.传统Otsu法在对梯度图像中的小目标分割时分割性能不佳,文中提出了一个Otsu阈值的改进算法,该算法使用快速计算Otsu阈值的新算法递归求解分割阈值.实验结果表明,与传统Otsu算法相比,计算Otsu阈值的快速算法速度更快,而阈值的改进算法对梯度图像中的小目标分割效果更好.