计算机应用 ›› 2012, Vol. 32 ›› Issue (04): 1133-1136.DOI: 10.3724/SP.J.1087.2012.01133

• 图形图像技术 • 上一篇    下一篇

弱边缘电荷耦合器件羊毛图像二值化算法

周理1,毕笃彦1,查宇飞2,罗宏凯3,何林远1   

  1. 1. 空军工程大学 工程学院,西安 710038
    2. 空军第二飞行学院 空中武器控制系,西安 710302
    3. 中国航空工业集团 第六三一研究所,西安 710068
  • 收稿日期:2011-10-25 修回日期:2011-12-02 发布日期:2012-04-20 出版日期:2012-04-01
  • 通讯作者: 周理
  • 作者简介:周理(1988-),男,湖南邵阳人,硕士研究生,主要研究方向:图像处理、计算机视觉;毕笃彦(1962-),男,陕西扶风人,教授,博士生导师,主要研究方向:图像处理、模式识别;查宇飞(1979-),男,湖北荆州人,讲师,博士,主要研究方向:图像处理、计算机视觉;罗宏凯(1985-),男,陕西西安人,研究员,硕士,主要研究方向:计算机硬件设计;何林远(1983-),男,河南洛阳人,讲师,硕士,主要研究方向:图像处理、模式识别。
  • 基金资助:
    航空科学基金资助项目(20095586016);国防科技重点实验室基金资助项目(9140C1004060903);国家自然科学基金资助项目

Binarization algorithm for CCD wool images with weak contour

ZHOU Li1,BI Du-yan1,ZHA Yu-fei2,LUO Hong-kai3,HE Lin-yuan1   

  1. 1. Engineering College, Air Force Engineering University, Xi’an Shaanxi 710038, China
    2. Department of Aerial Weapon-Dominating, Air Force Second Flying Academy, Xi’an Shaanxi 710032, China
    3. No.631 Research Institute, Chinese Aviation Industry Corporation, Xi’an Shaanxi 710068, China
  • Received:2011-10-25 Revised:2011-12-02 Online:2012-04-20 Published:2012-04-01
  • Contact: ZHOU Li

摘要: 为解决弱边缘图像二值化产生羊毛几何尺寸失真问题,通过对基于灰度和梯度指数的边缘细化算法研究,结合经典的全局阈值法和局部阈值法,提出了一种电荷耦合器件(CCD)羊毛图像自动二值化算法。该算法将sobel算子和斜坡边缘模型引入现有边缘细化算法中,既增加寻找边缘点环节又改进灰度调整因子,达到提高处理效率和避免人为干预的目的;在分析最大类间方差法和Bernsen法的基础上,结合全局和局部阈值处理各个子图像,从而强化边缘细节,降低失真度。实验结果表明,与传统方法相比,该算法对于弱边缘图像二值化具有良好的性能。

关键词: 羊毛细度测量, 图像二值化, 边缘宽度细化, sobel算子, 灰度调整因子, 斜坡模型, 最大类间方差法, Bernsen法

Abstract: In order to solve the distortion of wool geometric dimension, resulting from image binarization with weak contour, an automatic binarization algorithm for Charge-Coupled Device (CCD) wool image was proposed with reference to a ramp-width-reduction approach based on intensity and gradient indices, using a classical global threshold method and a local one. In that algorithm, edge-pixel-seeking step was added and gray-adjusting factor was improved, with sobel operator and ramp edge model introduced, to increase processing efficiency and avoid human intervention. Besides, every sub image was processed by the mixed global and local threshold based on the analysis of Otsus and Bernsens methods to intensify edge details and decrease distortion. Compared with the traditional ways, the experimental results show that the new algorithm has good performance in automatic binarization with weak contour.

Key words: wool diameter measurement, image binarization, ramp width reduction, sobel operator, gray-adjusting factor, ramp edge model, Otsu’s method, Bernsen’s method