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Journal of Information Science and Engineering, Vol. 23 No. 6, pp. 1955-1969 (November 2007)

An Intelligent Sensor Network for Object Detection, Classification and Recognition

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.

Keywords: surveillance system, sensor networks, support vector machine, pattern recognition

Full Text () Retrieve PDF document (200711_20.pdf)

Received November 11, 2005; revised March 24, July 7 & August 30, 2006; accepted September 27, 2006.
Communicated by Pau-Choo Chung.