基于OTSU的近红外图像分割的应用研究

大气与环境光学学报 ›› 2011, Vol. 6 ›› Issue (6): 470-475.

• 光学遥感与图像处理 • 上一篇

基于OTSU的近红外图像分割的应用研究

夏需堂¹，吴海滨^1，2，陈新兵¹，周德玉¹，周后伟¹，张铁译¹

1.安徽大学物理与材料科学学院，安徽合肥 230039；
2.安徽大学特种电视技术研究中心，安徽合肥 230088

出版日期:2011-11-28 发布日期:2011-11-18
作者简介:夏需堂（1986—），男，安徽无为人，汉族，安徽大学硕士研究生，主要研究方向为光电感测及图像处理等。Email：XIAxutang@gmail.com。*吴海滨（作者导师）（1962—），男，安徽大学硕士生导师，光电子专业硕士，教授级高工，1990年起，一直从事特种工业电视系列产品的开发设计及图像信息处理方面的研究工作，主持开发的多项特种电视产品填补了国内空白。Email：whb62@263.net
基金资助:
科技部创新基金项目（07C26213400516）。

Application Research of the Segmentation of Near-Infrared Image Based on OTSU

XIA Xu-Tang¹，WU Hai-Bin²，CHEN Xin-Bing¹，ZHOU De-Yu¹，ZHOU Hou-Wei¹，ZHAN GTie-Yi¹

1.School of Physics and Material Science, Anhui University, HeFei 230039, China;
2.The Research Center of Special TV Technology of Anhui University, Hefei 230088, China

Published:2011-11-28 Online:2011-11-18

摘要/Abstract

摘要：

OTSU法是最常用的利用图像的一维灰度直方图的阈值化方法之一，二维OTSU除了考虑像素点的灰度信息外还考虑了像素点与其邻域的空间信息。由于红外图像不同于一般灰度图像的一些特征，有针对性的采用了二维OTSU对其进行分割。通过与一维OTSU的相互比较可以看出，二维OTSU对近红外图像拥有更好的分割效果，能有效的分割出炉管图像，对后期的温度监测和声光报警具有重要的意义，提高了高温炉的安全性。

关键词: 直方图, OTSU, 近红外图像, 图像分割

Abstract:

OTSU is one of the most commonly used image–threshold methods, which based on one-dimension histogram of image’s gray level. The two-dimension OTSU takes the gray level of pixel point, as well as the spatial information between the pixel point and its field into consideration. Because of infrared image, different from the general characteristics of gray image, the two-dimensional OTSU segmentation is targeted adopted. According to the comparison with one-dimension OTSU, it is indicated that the two-dimension OTSU can segment the near-infrared image better and get the furnace image more effectively. By monitoring its temperature in the late period and alarming through sound and light, it greatly enhances the security of high- heat furnace.

Key words: histogram, OTSU, near-infrared image, image segmentation

夏需堂，吴海滨，陈新兵，周德玉，周后伟，张铁译. 基于OTSU的近红外图像分割的应用研究[J]. 大气与环境光学学报, 2011, 6(6): 470-475.

XIA Xu-Tang，WU Hai-Bin，CHEN Xin-Bing，ZHOU De-Yu，ZHOU Hou-Wei，ZHAN GTie-Yi. Application Research of the Segmentation of Near-Infrared Image Based on OTSU[J]. Journal of Atmospheric and Environmental Optics, 2011, 6(6): 470-475.

参考文献

[1] Otsu N. A threshold selection method from gray-level histograms [J]. IEEE Trans. on Syst. Madn. and Cybern., 1979, 9(1): 62-69. [2] Li Fan, Liu Shangqian, Hong Ming, et al. Algorithm of infrared image segmentation based on ant colony [J]. High Power Laser and Particle Beams, 2010, 22(5): 1005-1008(in Chinese). 李凡, 刘上乾, 洪鸣, 等. 基于人工蚁群的红外图像分割算法 [J]. 强激光与粒子束, 2010, 22(5): 1005-1008.
[3] Liu Jianzhuang, Li Wenqing. The automatic thresholding of gray-level pictures via two-dimensional Otsu method [J]. Acta Automatica Sinica, 1993, 19(1): 101-105(in Chinese). 刘健庄, 栗文青. 灰度图像的二维OTSU自动阈值分割方法 [J]. 自动化学报, 1993, 19(1): 101-105.
[4] Jing Xiaojun, Cai Anni, Sun Jing’ao. Image segmentation based on 2D maximum between-cluster variance
[J]. Journal of China Institute of Communications, 2001, 22(4): 71-76(in Chinese). 景晓军, 蔡安妮, 孙景鳌. 一种基于二维最大类方差的图像分割算法 [J]. 通信学报, 2001, 22(4): 71-76.
[5] Fan Jiulun, Zhao Feng. Two-dimensional Otsu’s curve thresholding segmentation method for gray-level images [J]. Acta Electronica Sinica, 2007, 35(4): 751-755(in Chinese). 范九伦, 赵凤. 灰度图像的二维OTSU曲线阈值分割法 [J]. 电子学报, 2007, 35(4): 751-755.
[6] Xiao Chaoyun, Zhu Weixing. Threshold selection algorithm for image segmentation based on Otsu rule and image entropy [J]. Computer Engineering, 2007, 33(14): 188-189(in Chinese) 肖超云, 朱伟兴. 基于OTSU准则及图像熵的阈值分割算法 [J]. 计算机工程, 2007, 33(14): 188-189.
[7] Zhang Yujin. Image Segmentation [M]. Beijing: Science Press House, 2001(in Chinese). 章毓晋. 图像分割 [M]. 北京: 科学出版社, 2001.
[8] Xia Jing, Sun Jiyin. Forward-looking infrared image segmentation based on region growing [J]. Laser & Infrared, 2011, 41(1):107-111(in Chinese). 夏晶, 孙继银. 基于区域生长的前视红外图像分割方法 [J]. 激光与红外, 2011, 41(1): 107-111.
[9] Wu Chengmao, Tian Xiaoping, Tan Tieniu. Fast iterative algorithm for two-dimensional Otsu thresholding method [J]. Pattem Recognition and Aitificial Intelligence, 2008, 21(6): 746-757(in Chinese). 吴成茂, 田小平, 谭铁牛. 二维OTSU阈值法的快速迭代算法 [J]. 模式识别与人工智能, 2008, 21(6): 746-757.

基于OTSU的近红外图像分割的应用研究

Application Research of the Segmentation of Near-Infrared Image Based on OTSU

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价

[1]	王振东江巨浪马宏亮程刚. 一种改进的雾天监控图像增强算法[J]. 大气与环境光学学报, 2018, 13(4): 309-314.
[2]	谢欣欣江伦张雷佟首峰李响. 天空背景光条件下空间激光通信系统粗跟踪光斑提取方法的研究[J]. 大气与环境光学学报, 2017, 12(3): 236-240.
[3]	吴海滨周雨润周英蔚陈新兵项龙飞李梓霂. 基于二维OTSU选取种子点的区域生长图像分割[J]. 大气与环境光学学报, 2013, 8(6): 448-453.
[4]	吴海滨周后伟张铁译陈新兵周雨润王哲. 基于OTSU的动态结合全局阈值的图像分割[J]. 大气与环境光学学报, 2012, (6): 463-468.