摘要
在图像分割中,门限的选取至关重要,本文在 Otsu 门限选择准则[1]的基础上,研究了一种基于图像熵的局部递归的门限选择及分割算法,该算法在图像背景不均或图像不是简单的单峰、双峰图像的情况下可以有效的分割,分割后图像的细节更加丰富,有利于分割后的特征提取。对几种不同的目标进行了实验,获得了较好的实验结果。
In image segmentation, the threshold selection is very important. In this thesis, a partial recursive algorithm of threshold selection and segmentation is put forward, which is based on the Otsu threshold selecting method. With this algorithm we can segment the image effectively even if the image is uneven and is not the single-modal or bimodal one. The segmentation result has more detail, which is good to the feature-extraction. Finally we make experiment with some sorts of images and obtain good result.
出处
《红外技术》
CSCD
北大核心
2004年第6期89-92,96,共5页
Infrared Technology
