Indoor Window Detection Based on Image Contour Analysis

doi:10.3969/j.issn.10062475.2018.04.011

Abstract

Abstract: Aiming to the problem of indoor window detection, this paper proposed an approach of indoor window detection based on image contour analysis. The image is preprocessed and a binary image is obtained by threshold segmentation and morphological processing. Then, the contours of the image are extracted by the border tracking based on the topology structure analysis, and stored as the sequence points. The contours of the qualifying conditions are selected according to the characteristics of the window contours. The minimum enclosing rectangles of each contour are figured up and the shortest distance between each two rectangles are calculated. Finally, the rectangles are classified and merged by the minimum spanning tree to obtain the position of the window. Experiment results show that the proposed method can effectively detect the windows in different indoor scenes.

Key words: window detection, threshold segmentation, binary image, contours extraction, minimum spanning tree

CLC Number:

TP391.41

KONG Qianqian, ZHAO Liaoying, ZHANG Li. Indoor Window Detection Based on Image Contour Analysis[J]. Computer and Modernization, doi: 10.3969/j.issn.10062475.2018.04.011.

References

［1］〖JP3〗Wang Ruisheng, Bach J, Ferrie F P. Window detection from mobile LiDAR data［C］// Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision. 2011:5865. 
［2］侯梦倩. 新中式风格的室内软装饰设计应用研究［D］. 杭州:浙江理工大学, 2016.
［3］ Recky M, Leberl F. Window detection in complex facades［C］// Proceedings of the 2nd European Workshop on Visual Information Processing. 2010:220225.
［4］ Miljanovic M, Eiter T, Egly U. Detection of windows in facades using image processing algorithms［J］. Indian Journal of Computer Scienceand Engineering, 2012,3(4):539547.
［5］ Ali H, Seifert C, Jindal N, et al. Windowdetection in facades［C］// Proceedings of the 14th International Conference on Image Analysis and Processing. 2007:837842.
［6］〖JX-+0.3mm〗〖XCC1.TIF〗〖KG-0.3mm〗〖JX+0.3mm〗ech J, ára R. Windowpane detection based on maximum aposteriori probability labeling［C］// Proceedings of the 12th International Workshop on Combinatorial Image Analysis. 2008:311.
［7］〖KG-*4〗〖JP3〗Mesolongitis A, Stamos I. Detection of windows in point clouds of urban scenes［C］// Proceedings of the 2012 IEEE Computer Society Conference on Computer Vision and 〖JP3〗Pattern Recognition Workshops. 2012, doi: 10.1109/CVPRW.2012.6238910. 
［8］缪君,储珺,张桂梅. 基于图像边缘与玻璃属性约束的窗户检测［J］. 图学学报, 2015,36(5):776782.
［9］贾凯华,李和志,吴泽敏. 一种新的窗户特征提取方法研究［J］. 测绘工程, 2016,25(10):6468.
［10］周茗琪. 基于显著度的图像灰度化算法研究［D］. 上海:上海交通大学, 2015.
［11］ Otsu N.A threshold selection method from graylevel histograms［J］. IEEE Transactions on Systems, Man, and Cybernetics, 1979,9(1):6266. 
［12］蔡剑. 基于数学形态学的图像椒盐噪声去除方法［J］. 电子设计工程, 2016,24(13):182184.
［13］Suzuki S,Abe K. Topological structural analysis of digitized binary images by border following［J］. Computer Vision, Graphics, and Image Processing, 1985,30(1):3246.
［14］李洋,李岳阳. 一种快速提取植物叶片最小外接矩形的算法［J］. 江南大学学报(自然科学版), 2015,14(3):273277.
［15］Jana P K, Naik A. An efficient minimum spanning tree based clustering algorithm［C］// Proceedings of the 2009 〖JP3〗International Conference on Methods and Models in Computer Science. 2009, doi: 10.1109/ICM2CS.2009.5397966. 
［16］袁威威. 应用Kruskal的改进算法求最小生成树［J］. 江苏第二师范学院学报(自然科学版), 2017,33(6):1213.
［17］胡涛,吕虹,孙小虎,等. 基于水平垂直灰度开运算的车牌字符分割算法［J］. 电子技术应用, 2012,38(10):109111.

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