Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (11): 176-178.DOI: 10.3778/j.issn.1002-8331.2010.11.054

• 图形、图像、模式识别 • Previous Articles     Next Articles

Multi-threshhold segmentation and optimization based on Otsu in color image

LI Zhong-jian,DU Juan,GUO Lu   

  1. College of Automation,Northwest Polytecnical University,Xi’an 710072,China
  • Received:2008-10-07 Revised:2008-12-26 Online:2010-04-11 Published:2010-04-11
  • Contact: LI Zhong-jian

将Otsu用于多阈值彩色图像分割的方法及优化

李中健,杜 娟,郭 璐   

  1. 西北工业大学 自动化学院,西安 710072
  • 通讯作者: 李中健

Abstract: As it is of deficiency that the conventional Otsu algorithm is only applicable to single-threshold,the algorithm is extended to multi-threshold color image segmentation.Firstly,the selection of meaningful peak values among a group of maximum values is carried out.Then,according to the peak values,the diagram is divided into a certain number of segmentation intervals,in which the threshold is selected.Based on methodology of morphology,the segmentation is optimized.And the influence,as a result of ignoring the characteristics of space,which the threshold technique imposes on noises,is lessened.The results of the experiment indicate that the Otsu algorithm based on multi-threshold color image segmentation is able to implement automatic and rapid multi-threshold segmentation,and is noise-resistant to some extent.

Key words: color quantization, multi-threshold, the meaning peak, morphology

摘要: 针对传统Otsu算法只用于单阈值分割的不足,将Otsu算法推广到多阈值彩色图像分割中,提出先在众多极大值中寻找有意义峰值,根据峰值将直方图划分成多个待分割区间,再在每个区间进行阈值选取的方法;并且综合运用了形态学的方法对分割结果进行优化,降低阈值法因不考虑图像空间特性而造成的对噪声敏感的影响。实验结果表明,该方法能自动而快速地对彩色图像进行多阈值分割,而且具有较强的抗噪能力。

关键词: 颜色量化, 多阈值, 有意义峰值, 形态学

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