一种改进的保矩自动阈值图像分割算法

Shi-tu Luo, Qi Zhang, F. Luo, Yanling Wang, Zhiyong Chen
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引用次数: 9

摘要

在对直方图为单峰或单调函数的图像进行分割时,由于存在严重的背景干扰,分割精度受目标大小方差的影响较大,因此本文提出了一种改进的保持矩自动阈值算法。针对原有算法忽略图像细节的不足,该算法利用目标边界与相邻背景灰度差大而目标区域或背景区域像素差小的特点,在保持矩的自动阈值分割中加入基于目标边缘像素的梯度调整,从而在分割结果中兼顾图像的整体和细节。该算法不需要迭代和搜索,速度快,可以满足实时性的要求。仿真结果表明,该算法能有效分割目标图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved moment-preserving auto threshold image segmentation algorithm
When moment-preserving auto threshold algorithm is used to segment image whose histogram is unimodal or monotonic function, there is serious background interference, and the segmentation accuracy is greatly affected by the size variance of the object, so this paper puts forward an improved moment-preserving auto threshold algorithm. Aiming at the original algorithm's shortage of neglecting image details, this algorithm takes advantage of the feature that the grey level difference between object borders and adjacent background is great while the difference among pixels in an object region or background region is small, and then adds gradient adjustment based on object edge pixels to moment-preserving auto thresholding, in order to look after both the whole and the details of image in segmentation result. This algorithm needs no iteration or search, and it is fast enough to satisfy the demand for real time. As simulation results show, this algorithm can segment object image effectively.
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