一种基于模糊决策的矩形目标提取算法

毛峡; 赵兴圆; 沈巍

一种基于模糊决策的矩形目标提取算法

北京航空航天大学电子信息工程学院, 北京 100191

详细信息

中图分类号: TP 391
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- 被引次数: 0
出版历程
- 收稿日期: 2007-05-22
- 网络出版日期: 2008-06-30

Extraction method of rectangular building based on fussy decision-making

School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

摘要

摘要: 航空图片中的城市建筑物屋顶一般为矩形或平行四边形,能准确而快速地提取矩形,无论在军事上还是民用上都具有非常重要的意义.针对从航空图像中自动提取矩形建筑物目标的问题,提出了一种基于模糊决策的矩形目标提取方法.首先根据直线提取方法得到的直线特征集生成假设矩形空间,进而采用模糊数学方法进行证据融合得到决策信息,并对生成的假设矩形进行选择与验证,得到矩形目标结构特征.实验结果表明,该算法避免了固定阈值的设定,适应性强,鲁棒性好,有较强的实际应用价值.
- 矩形建筑物 /
- 感知分组 /
- 模糊决策 /
- 阈值
Abstract: The roof of the building in aerial image is generally rectangle or parallelogram. It makes a significance sense to extract the rectangle accurately and fast, either in military aspect or in civilian aspect.A method based on fussy decision-making for extraction of rectangular buildings from the aerial images was proposed. Firstly, the presumed rectangular space was generated via line feature, which was resulted from beeline-extraction of the aerial image. Then, the support evidences which were get from the image were combined by fussy mathematic method in order to obtain decision-making information.Finally, the generated rectangle was selected and validated according to the decision-making information. This arithmetic uses the non-fixed threshold value to select the supporting evidences to improve the validity. The results of performance assessment also possess the robustness and high extraction rate of the approach developed.
- rectangle building /
- perceptual grouping /
- fussy decision-making /
- threshold

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参考文献(1)

[1] 陶文兵,田岩,张钧,等. 航空图像矩形建筑物自动提取方法研究[J].宇航学报,2003,24(4):341-348 Tao Wenbing, Tian Yan, Zhang Jun,et al. The technique for automated rectangle building extraction from aerial images[J]. Journal of Astronautics, 2003,24(4):341-348(in Chinese) [2] 张煜,张祖勋,张剑清.几何约束与影像分割相结合的快速半自动房屋提取[J].武汉测绘科技大学学报,2000,25(3):238-242 Zhang Yu, Zhang Zuxun, Zhang Jianqing. House semi-automatic extraction based on integration of geometrical constraints and image segmentation[J]. Journal of Wuhan Technical University of Surveying and Mapping,2000,25(3):238-242(in Chinese) [3] 周俊,晏非,孙曼. 基于区域分割合并的建筑物半自动提取方法[J].海洋测绘,2005,25(1):58-60 Zhou Jun, Yan Fei, Sun Man. Semi-automatic extraction of building based on region segmenting and merging[J]. Hydrographic Surveying and Charting,2005,25(1):58-60(in Chinese) [4] Huertas A, Nevatia R. Detection building in aerial images [J]. Computer Vision,Graphics and Image Processing , 1988 , 41 (2) :131-152 [5] Lin C, Huertas A, Nevatia R. Detection of building using perceptual grouping and shadows IEEE Proceeding of Computer Vision and Pattern Recognition. Seattle, WA:IEEE Press,1994:62-69 [6] Xie Minghong, Fu Kun, Wu Yirong. Building recognition and reconstruction from aerial imagery and LIDAR data Radar 2006 CIE-06 International Conference. Shanghai:, 2006:1-4 [7] Canny. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,1986,8(6):679-698 [8] 曹谢东.模糊信息处理及应用[M].北京:科学出版社, 2003 Cao Xiedong. Fuzzy information proceeding and application [M].Beijing:Science Press,2003(in Chinese)

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