Man-made Object Detection Based on Texture Clustering and Geometric Structure Feature Extracting

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Fei Cai 1,* Honghui Chen 1 Jianwei Ma 1

1. Key Laboratory for Information System Engineering, School of Information System and Management, National University of Defense Technology, Changsha, China

* Corresponding author.


Received: 3 Aug. 2010 / Revised: 12 Oct. 2010 / Accepted: 2 Jan. 2011 / Published: 8 Mar. 2011

Index Terms

Man-made object detection, image segmentation, object marking, feature extraction, texture clustering


Automatic aerial image interpretation is one of new rising high-tech application fields, and it’s proverbially applied in the military domain. Based on human visual attention mechanism and texture visual perception, this paper proposes a new approach for man-made object detection and marking by extracting texture and geometry structure features. After clustering the texture feature to realize effective image segmentation, geometry structure feature is obtained to achieve final detection and marking. Thus a man-made object detection methodology is designed, by which typical man-made objects in complex natural background, including airplanes, tanks and vehicles can be detected. The experiments sustain that the proposed method is effective and rational.

Cite This Paper

Fei Cai, Honghui Chen, Jianwei Ma, "Man-made Object Detection Based on Texture Clustering and Geometric Structure Feature Extracting", International Journal of Information Technology and Computer Science(IJITCS), vol.3, no.2, pp.9-16, 2011. DOI: 10.5815/ijitcs.2011.02.02


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