Title :
Target Recognition using Bayesian Data Fusion Method
Author :
Sun, Yu-Qiu ; Tian, Jin-Wen ; Liu, Jian
Author_Institution :
Sch. of Inf. & Math., Yangtze Univ., Jingzhou
Abstract :
Multisensor information plays an important pole in the target recognition and other application fields. Fusion performance is tightly depended on the fusion level selected and the approach used. Feature level fusion is a potential and difficult fusion level. Bayesian fusion method is an important theory in feature level. A new method is presented to fuse infrared images and recognize object in the paper. Firstly, Bayesian principles, fusion mode and recognition decision function are described. Then, aiming at the features of mid-wave infrared image and long-wave infrared image, we use Bayesian probability to fuse them. Last, recognize target and background obtained with training and test pattern vectors. The experiment results show stability and feasibility of the fusion recognition using Bayesian decision theory in infrared image
Keywords :
Bayes methods; decision theory; image recognition; infrared imaging; object recognition; probability; sensor fusion; Bayesian data fusion; Bayesian decision theory; Bayesian probability; feature level fusion; long-wave infrared image; mid-wave infrared image; multisensor information; object recognition; target recognition; Bayesian methods; Cybernetics; Data mining; Fuses; Image fusion; Image processing; Image recognition; Infrared imaging; Laboratories; Machine learning; Sensor fusion; Target recognition; Bayesian decision; data fusion; infrared images; target recognition;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258461