Please wait a minute...


Remote Sensing Technology and Application  2009, Vol. 24 Issue (3): 379-384    DOI: 10.11873/j.issn.1004-0323.2009.3.379
A Method of Airport Shelter Detection Based onFeature Fusion in Remote Sensing Images
SUN Jun-ling,CHEN Tian-ze,SU Yi
(Department of Electronic Science and Engineering,National University of Deffense Technology,Changsha 410073,China)
Download:  PDF (1352KB) 
Export:  BibTeX | EndNote (RIS)      

Combining the features of position and shape,the method of detecting the airport shelter in remote sensing images is proposed in this paper.Firstly,the Mathematics Morphology to extract the skeleton of airport road networks was introduced in preprocessing step.Then topological relationship of the net is employed to locate the End Road of shelter targets,which can indicate the position well.In succession,contour sequence moments are used as salience features to extract building shapes.On that basis,the fusion detection of shelters can be achieved.The experiment is carried out with high resolution satellite images of airport; the results show that this method can recognize the shelters in airport area accurately.

Key words:  End road feature      Contour sequence moments      Feature fusion      Target detection     
Received:  07 January 2009      Published:  20 January 2010
TP 75  
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
Articles by authors

Cite this article: 

SUN Jun-ling,CHEN Tian-ze,SU Yi. A Method of Airport Shelter Detection Based onFeature Fusion in Remote Sensing Images. Remote Sensing Technology and Application, 2009, 24(3): 379-384.

URL:     OR

[1]    Druyts P,Mees W,Borghys D,et al.SAHARA:Semi-automatic Help for Region Analysis[C].Proceedings of the Joint Workshop of ISPRS Working Groups I/1,I/3 and IVA:Sensors and Mapping from Space.Germany Hannover,1997:267-274. 
[2] Ye Bin,Peng Jiaxiong.Recognition and Understanding of Airfield Based on the Structure Feature[J].Journal of Huazhong University of Science and Technology,2001,29(3):39-42.[叶斌,彭嘉雄.基于结构特征的军用机场识别与理解[J].华中科技大学学报,2001,29(3):39-42.]
[3] Jean-Marc G,Jean Louis A.Artificial Intelligence for Networks Recognition in Remote Sensing Images[J].SPIE,Computer Vision for Industy,1993,1989:275-285.
[4]   Yang Bo.A Method of Image Segmentation Based on Genetic Algorithms of Maximum Between-cluster Variance[J].Journal of Hunan Normal University:Natural Science Eedition,2003,26(1):32-36.[阳波.基于最大类间方差遗传算法的图像分割方法[J].湖南师范大学学报:自然科学版,2003,26(1):32-36.] 
[5] An Ru,Feng Xuezhi,Wang Huilin.Road Feature Extraction form Remote Sensing Classified Imagery Based on Mathematical Morphology and Analysis of Road Networks[J].Journal of China Image and Graphics,2003,8(7):800-801.[安如,冯学智,王慧麟.基于数学形态学的道路遥感影像特征提取及网络分析[J].中国图像图形学报,2003,8(7):800-801.]
[6] Jia Yunde.Computer Vision[M].Beijing:Science Press,2000.[贾云得.机器视觉[M].北京:科学出版社,2000.]
[7] Lan Pinbiao,Lin Ziyang,Huang Letian.A Thinning Algorithm for Binary Images Based on Deletion of Edge-Points and Reservation of Inner-points[J].Computer Engineering and Design,1999,20(3):59-63.[兰品标,林子扬,黄乐天.一种基于内点保留和边缘点删除的二值图像细化算法[J].计算机工程与设计,1999,20(3):59-63.]
[8]   Hu M K.Visual Pattern Recognition by Moment Invariants[J].IEEE Transactions on Information Theory,1962,8(2):179-187. 
[9] Gupta L,Srinath M D.Contour Sequence Moments for the Classification of Closed Planar Shapes[J].Pattern Recogniton,1987,20(3):267-272. 
No Suggested Reading articles found!