利用二维属性直方图的Otsu自动阈值分割方法

Automatic Thresholding Using the Otsu Algorithm Based on the Two-Dimensional Bound Histogram

提出了二维属性直方图的概念,进而提出了一种基于二维属性直方图的图像自动阈值化方法。该方法通过构造属性集,确定相应的二维属性直方图,利用二维属性直方图的Otsu算法确定灰度阈值。为了说明该方法的适用性和性能,将其用于一种海底小目标图像阈值化。作为比较,也给出了利用一维属性直方图的Otsu算法阈值化的结果。结果表明:该方法适用于直方图不是理想双峰形状的图像,它比一维属性直方图的Otsu算法抗干扰性更强,分割效果更好。

The concept of the two-dimensional bound histogram is proposed, and an automatic threshold selection method based on that histogram is presented. In the method, the bound set of an image and its corresponding two-dimensional bound histogram are constructed and the gray-level threshold for segmentation is determined by the Otsu algorithm based on that histogram. In order to prove the validity of the method, it was applied to thresholding of the image of a small underwater target. The Otsu algorithm based on the one-dimensional bound histogram was also used. The results show that the former, the proposed method, is well applicable to the image with a non-ideal bimodal histogram, and has better antinoise performance and segmental effect than the latter.