计算机工程

• 图形图像处理 • 上一篇    下一篇

基于HSV色彩模型与区域生长法的水文图像分割

冷建伟 1,沈芳婷 2   

  1. (1.天津市复杂系统控制理论及应用重点实验室,天津 300384; 2.天津理工大学 自动化学院,天津 300384)
  • 收稿日期:2016-06-03 出版日期:2017-07-15 发布日期:2017-07-15
  • 作者简介:冷建伟(1961—),男,教授,主研方向为图像分割、计算机控制系统;沈芳婷,硕士研究生。

Hydrological Image Segmentation Based on HSV Color Model and Region Growing Algorithm

LENG Jianwei  1,SHEN Fangting  2   

  1. (1.Tianjin Key Laboratory for Control Theory and Applications in Complicated Industry Systems,Tianjin 300384,China; 2.School of Electrical Engineering,Tianjin University of Technology,Tianjin 300384,China)
  • Received:2016-06-03 Online:2017-07-15 Published:2017-07-15

摘要: 针对水文监测过程中视频图像信噪比高、观测目标颜色特征明显以及目标区域位置关系特定等特点,提出一种改进的水文图像分割方法。通过将HSV色彩模型划分为量化区间,三维颜色信息转换成一维数组,对HSV模型的明度分量进行二次量化,从而根据颜色区域进行优化分割。在此基础上,利用改进的区域生长法得到当前水位值,实现水文图像的分割。实验结果表明,该方法能够快速分割出目标区域,并且解决了水文图像像素间的连通性和邻近性问题。

关键词: 水文图像, 彩色图像分割, HSV色彩模型, 色彩量化, 区域生长法

Abstract: Aiming at the characteristics of the hydrological monitoring video images,such as the high Signal to Noise Ratio(SNR),obvious color differences among targets and the specific location of target regions,an improved method for segmenting the hydrological image is proposed.By dividing the HSV color model into quantization intervals,the three-dimensional color information is changed into a one-dimensional array.To optimize the segmentation results based on the color only,the secondary quantizing of the Value component of HSV model takes place.Based on this,the current water level is obtained by using the improved region growing method.Finally,the segmentation of hydrological image is realized.The experimental results show that the method can segment the target area quickly and solve the connectivity and proximity problems between pixels in the hydrological image.

Key words: hydrological image, color image segmentation, HSV color model, color quantization, region growing algorithm

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