Moving Object Recognition By Neural Fuzzy Network For Visual Surveillance System
نویسندگان
چکیده
Moving object recognition by shapebased neural fuzzy network is proposed in this paper. The moving objects considered in this paper include pedestrians, cars, motorcycles, and dogs. Given the shape of the moving object, we calculate its contour. The distance between the contour center and each contour point is calculated and smoothed. Parts of the feature vectors are obtained from discrete Fourier transform coefficients of the smoothed distance. The other feature is the length-width ratio of the object’s shape, which is derived from vertical and horizontal projection of the shape of the object. Based on the feature vector, we use the Self-cOnstructing Neural Fuzzy Inference Network (SONFIN) for recognition. The experiment shows that SONFIN recognizes moving objects with high accuracy. The performance of SONFIN is also shown to be better than a neural network.
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