Target recognition and tracking based on data fusion and data mining

Jie Yang; Ying Hu; Guozheng Li

doi:10.1117/12.440293

18 September 2001 Target recognition and tracking based on data fusion and data mining

Jie Yang, Ying Hu, Guozheng Li

Proceedings Volume 4556, Data Mining and Applications; (2001) https://doi.org/10.1117/12.440293
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

A system for target recognition and tracking based on radar and infrared image sensors is presented, which can make use of the complement and redundancy of data from different sensors to improve the precision of target recognition and tracking and the robustness and reliability. For data fusion at characteristic level, characteristics of a target obtained from radar can be used in the IR image-based subsystem to improve the ability of object recognition, and vice versa. The process of target recognition based on IR image analysis is composed of image enhancement, image segmentation and recognition of segmented images. The recognition of segmented objects is divided into two classes: recognition of dot targets and area targets.

Citation Download Citation

Jie Yang, Ying Hu, and Guozheng Li "Target recognition and tracking based on data fusion and data mining", Proc. SPIE 4556, Data Mining and Applications, (18 September 2001); https://doi.org/10.1117/12.440293

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