Keywords: surveillance system, sensor networks, support vector machine, pattern recognition
Received November 11, 2005; revised March 24, July 7 & August 30, 2006; accepted September 27, 2006.
Communicated by Pau-Choo Chung.
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Frank Y. Shih, Yi-Ta Wu, Chao-Fa Chuang, Jiann-Liang Chen1, Hsi-Feng Lu1 and Yao-Chung Chang2
Computer Vision Laboratory, College of Computing Sciences
New Jersey Institute of Technology
Newark, New Jersey 07102, U.S.A.
1Department of Computer Science and Information Engineering
National Dong Hwa University
Hualien, 974 Taiwan
2Department of Information Management
National Taitung University
Taitung, 684 Taiwan
In this paper, an intelligent sensor network is developed for object detection, classification
and recognition. We utilize wireless sensors as the first layer to detect coordinates
of moving objects in a secured area. Cameras are activated to capture image features
for object classification and recognition. In order to reduce processing time, a hierarchical
image extraction approach is developed. Global object features such as size and
motion are acquired for classifying objects into a number of classes. If the moving object
is considered suspicious, the cameras will be requested to capture detailed images for
object recognition. Experimental results show that our system can achieve a high face
recognition rate of 95.4% for the testing images captured by the surveillance system.
Received November 11, 2005; revised March 24, July 7 & August 30, 2006; accepted September 27, 2006.
Communicated by Pau-Choo Chung.