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Remote Sensing Technology and Application  2012, Vol. 27 Issue (2): 190-196    DOI: 10.11873/j.issn.1004-0323.2012.2.190
Research of Urban Building Recognition Method based on Line Features Matching
Li Songlin1,Fan Haisheng2,Chen Xiuwan1
(1.Institution of Remote Sensing and GIS,Peking University,Beijing 100871,China;2.Research Center of Remote Sensing Cloud Services,Institute of Remote Sensing Application,Chinese Academy of Sciences,Dongguan 520808,China)
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With the popularity of cell phones having functions of GPS positioning,navigation and camera,there exist increasing demands for real-time identification of urban buildings with mobile terminals.In this paper,image processing algorithms for urban buildings recognition,including SIFT and Local Search,were discussed and compared in details to show that contour lines and their combinations are stable geometric features of buildings,so the algorithms based on contour lines immune to affine transformation,low picture qualities and lens distortion.Besides,the match index based on contour lines can reflect the camera position change.As a result,Local Search was improved;firstly getting the building contour lines by abstracted from pictures photographed by mobile terminals and generated from the 3D-database,secondly utilizing it to find some of the best matches between  those contour lines.The improved algorithm can meet the demand of fast building recognition in mobile terminals .

Key words:  Urban building recognition      SIFT      Local Search      Line features matching      Sky-line of construction     
Received:  11 April 2011      Published:  23 January 2013
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Li Songlin,Fan Haisheng,Chen Xiuwan. Research of Urban Building Recognition Method based on Line Features Matching. Remote Sensing Technology and Application, 2012, 27(2): 190-196.

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[1]Yeh T,Lee J J,Darrell T.Fast Concurrent Object Localization and Recognition[C]//IEEE Conference on Computer Vision and Pattern Recognition,Miami,2009:280-287.
[2]Lindeberg T.Scale-space Theory:A Basic Tool for Analysing Structures at Different Scales[J].Journal of Applied Statistics,1994,21(1&2):225-270.
[3]Lowe D G.Distinctive Image Features from Scale-Invariant Keypoints[J].International Journal on Computer Vision,2004,60(2):91-110.
[4]Feng Jingkuai.City Geographical Position Recognition System base on SIFT Feature Matching Algorithm[J].Computer & Telecommunication,2009,8:53-55.[冯镜蒯.基于SIFT特征匹配算法的城市地点识别系统[J].电脑与电信,2009,8:53-55.]
[5]Jin Taisong,Li Cuihua,Wei Benjie.Approach to Building Recognition[J].Computer Engineering and Application,2009,42(33):1-3.[金泰松,李翠华,魏本杰.一种建筑物目标识别方法[J].计算机工程与应用,2009,42(33):1-3.]
[6]Jin Taisong,Ye Congyin,Li Cuihua,et al.Approach to Building Recognition in Complex Scenes[J].Computer Engineering,2007,33(6):198-200.[金泰松,叶聪颖,李翠华,等.一种复杂场景下建筑目标识别方法[J].计算机工程,2007,33(6):198-200.]
[7]Wang Zheshen,Li Cuihua.Improved Classical Hough Transform Applied to Building Detection and Recognition[J].Journal of Image and Graphics,2005,10(4):463-467.[汪哲慎,李翠华.基于改进Hough变换的建筑目标搜索与识别[J].中国图象图形学报,2005,10(4):463-467.]
[8]Wang Junqiu,Zha Hongbin.Combining Interest Points and Edges for Building and Object Recognition[J].Journal of Computer Aided Design & Computer Graphics,2006,18(8):1257-1263.[王君秋,查红彬.结合兴趣点和边缘的建筑物和物体识别方法[J].计算机辅助设计与图形学学报,2006,18(8):1257-1263.]
[9]Beveridge J R.Local Search Algorithms for Geometric Object Recognition;Optimal Correspondence and Pose[D].Amherst:University of Massachusetts,1993.
[10]Canny J.A Computational Approach to Edge Detection[J].IEEE Transaction on Pattern Analysis and Machine Intelligence,1996,8:679-698.

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