Object recognition is often performed in an environment full of uncertainties. Typical factors are the imprecision introduced by the limitations of image processing algorithms, the misinterpretation of the feature vector due to noise or occlusion, and the infinite variability of the object features due to continuous environment change as well as countermeasures. An integrated approach (statistical methods, multi-sensor fusion and fuzzy logic) for automatic object recognition is presented in this paper. A fuzzy scene representation is proposed to cope with uncertainties. The features of the object and the background are obtained from both a priory knowledge and the data collected by a multi-sensor suite and then reconstructed for object recognition.
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