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Vol. 160, Issue 12, December 2013, pp. 220-228




Experiments of Road Vehicle Detection Using Very High-resolution Remote Sensing Images
* Qulin TAN, Hao WANG

Photogrammetric Engineering & Remote Sensing, School of Civil Engineering, Beijing Jiaotong University, Beijing, 100044, China

* Tel.: 086-010-51688207, fax: 086-010-51683764

* E-mail: qltanbjtu@163.com


Received: 13 October 2013   /Accepted: 22 November 2013   /Published: 30 December 2013

Digital Sensors and Sensor Sysstems


Abstract: Road vehicle detection using very high-resolution remote sensing images has a unique advantage of covering a large area at the same time over all ground-based detectors. But the detection of small vehicle-object in remote sensing imagery is still a challenging task. A scheme was proposed to detect road vehicle objects from airborne color digital orthoimagery based on image segmentation and fuzzy logic classification. Firstly, a vector-generated road mask was used to constrain detection of vehicles to road region. Secondly, image segmentation algorithm was performed to form image objects in the preprocessing orthoimagery. Finally, based on a set of fuzzy logic rules defined by membership functions, vehicle objects were detected and separated from other objects. A representative set of road segment images was selected from available images to test the proposed scheme. Experimental results indicate that the detection rates of all test road-segments are high with very few false alarms.


Keywords: Remote sensing, Vehicle detection, Segmentation, Fuzzy logic, Classification.


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