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Remote Sensing Technology and Application  2013, Vol. 28 Issue (2): 240-244    DOI: 10.11873/j.issn.1004-0323.2013.2.240
    
A Method to Detect Tower Cranes based on Self-adaptive Weight Mathematical Morphology
Yu Bo1,2,Niu Zheng1,Wang Li1,Liu Yaqi3,Chen Fang4
(1.The State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and
Digital Earth,Chinese Academy of Sciences,Beijing 100101,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China;
3.Beihang University,Beijing 100191,China;4.Laboratory of Digital Sciences,Institute of
Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China)
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Abstract  

Tower cranes,as landmarks of construction sites,are alerts of illegal buildings and powerful basis of engineering process.H〖JP2〗owever,it’s very difficult to extract tower cranes exactly,because the background objects in urban remote sensed images are complexed and the influence of noise is severe.Moreover,there have not been any algorithms available in detecting tower cranes.The different tower cranes may have the influences in multi-directional and multi-scale structuring elements on the image,a method to detect tower cranes based on mathematical morphology with self-adaptive weight is put forward in this paper.It is adopted to do segmentation with Unmanned Aviation Vehicle Remote Sensing (UAVRS) image in our study.The weight is determined automatically based on the filling times that the structuring element has processed the image.Binarization,edge detection,line extraction and finally recognizing  tower cranes precisely based on their specific geometrical characteristics are conducted.It has been revealed that this method can be feasible to segment aviation images and extract relative features.Moreover,it has important applications in evaluating investment in urban construction.

Key words:  Image segmentation      Morphology      Tower cranes      Self-adaptive     
Received:  12 March 2012      Published:  24 June 2013
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Yu Bo
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Chen Fang

Cite this article: 

Yu Bo,Niu Zheng,Wang Li,Liu Yaqi,Chen Fang. A Method to Detect Tower Cranes based on Self-adaptive Weight Mathematical Morphology. Remote Sensing Technology and Application, 2013, 28(2): 240-244.

URL: 

http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2013.2.240     OR     http://www.rsta.ac.cn/EN/Y2013/V28/I2/240

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