Unsupervised background-constrained tank segmentation of infrared images in complex background based on the Otsu method.
In an effort to implement fast and effective tank segmentation from infrared images in complex background, the threshold of the maximum between-class variance method (i.e., the Otsu method) is analyzed and the working mechanism of the Otsu method is discussed. Subsequently, a fast and effective method for tank segmentation from infrared images in complex background is proposed based on the Otsu method via constraining the complex background of the image. Considering the complexity of background, the original image is firstly divided into three classes of target region, middle background and lower background via maximizing the sum of their between-class variances. Then, the unsupervised background constraint is implemented based on the within-class variance of target region and hence the original image can be simplified. Finally, the Otsu method is applied to simplified image for threshold selection. Experimental results on a variety of tank infrared images (880 × 480 pixels) in complex background demonstrate that the proposed method enjoys better segmentation performance and even could be comparative with the manual segmentation in segmented results. In addition, its average running time is only 9.22 ms, implying the new method with good performance in real time processing.
Electronic Engineering Department, Shijiazhuang Mechanical Engineering College, Heping Road, Shijiazhuang City, 050003 China ; 66393 Postdoctoral Science Research Workstation, Qiyi Road, Hebei Baoding City, 071000 China.
Yulong
Y
Zhou
Electronic Engineering Department, Shijiazhuang Mechanical Engineering College, Heping Road, Shijiazhuang City, 050003 China.
Min
M
Gao
Electronic Engineering Department, Shijiazhuang Mechanical Engineering College, Heping Road, Shijiazhuang City, 050003 China.
Dan
D
Fang
State Grid Hebei Electronic Power Company Maintenance Branch, XinHua Region, Zhongsheng Road No. 66, Shijiazhuang, 050071 China.
Baoquan
B
Zhang
Background constraint; Infrared images in complex background; Tank segmentation; The Otsu method; Threshold analysis