阈值分割是众多图像分割方法中使用最普遍的一种方法,阈值的求解也是图像处理的重心.传统Otsu算法属于穷举式的阈值求解方法,需遍历每个灰度值并计算以其为阈值的类间方差,在此进行了大量不必要的计算,可能无法应用于某些实时性要求较高的环境中.对此提出一种快速的Otsu改进算法,在引入图像复杂度及其相关性质缩小了灰度的搜索范围,同时在搜索范围内使用了一种快速计算方法,较传统Otsu算法进行了二次加速.实验结果证明,该算法较传统Otsu算法提高了计算速度,且两种算法的图像分割结果相同.%Threshold segmentation is one of the most commonly used image segmentation methods,and the solution of threshold is also the focus of image processing. The traditional Otsu algorithm is an exhaustive threshold solution method,which needs to traverse each gray value,calculate the interclass variance taking the gray value as the threshold value,and make a large number of unnecessary calculations. As a result,the traditional Otsu algorithm may not be appropriate to be applied in some environments with high real-time performance requirements. Therefore,an improved fast Otsu algorithm is proposed. The hunting scope of the traversed gray was reduced after importing the image complexity and its related properties. A fast calcula-tion method is used in the scope of the traversed gray,which executes secondary acceleration in comparison with the traditional Otsu algorithm.The experimental results show that this algorithm improves the calculation speed in comparison with the traditional Otsu algorithm,and the image segmentation results of the two algorithms are the same.
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