计算机工程 ›› 2007, Vol. 33 ›› Issue (14): 188-189,.doi: 10.3969/j.issn.1000-3428.2007.14.066

• 人工智能及识别技术 • 上一篇    下一篇

基于Otsu准则及图像熵的阈值分割算法

肖超云,朱伟兴   

  1. (江苏大学电气信息工程学院,镇江 212013)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-07-20 发布日期:2007-07-20

Threshold Selection Algorithm for Image Segmentation Based on Otsu Rule and Image Entropy

XIAO Chaoyun, ZHU Weixing   

  1. (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013)
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-07-20 Published:2007-07-20

摘要: 在图像分割中,阈值的选取至关重要,在经典的Otsu准则基础上,结合图像熵提出了一种改进的局部递归的阈值选取及分割算法。基于图像像素熵信息,运用递归思想局部搜索图像的最佳阈值,这样不但缩短了计算时间,而且具有较好的自适应特点。该算法在图像背景不均匀或图像不是简单的单峰、双峰图像的情况下可以进行有效的分割,分割后的图像细节更加丰富,有利于分割后的特征提取。对Lena图像进行了实验,获得了较好的分割结果。

关键词: 图像分割, Otsu准则, 阈值,

Abstract: In image segmentation, threshold selection is very important. A partial recursive algorithm of threshold selection and segmentation is put forward, which is based on the Otsu threshold selecting method. Based on the information of entropy of image pixels, a partial recursive algorithm is used to search optical threshold. It not only reduces the running time, but also has better self-adaptability. With this algorithm, the image can be segmented effectively even if it is uneven and not the single-modal or bimodal one. The segmentation result has more details, which is good to the feature extraction. An experiment with Lena image is made and good result is obtained.

Key words: image segmentation, Otsu rule, threshold, entropy

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