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Recognition of characters on car number plate and best recognition ratio among their layers using Multi-layer Perceptron
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 Title & Authors
Recognition of characters on car number plate and best recognition ratio among their layers using Multi-layer Perceptron
Lee, Eui-Chul; Lee, Wang-Heon;
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 Abstract
The Car License Plate Recognition(: CLPR) is required in searching the hit-and-run car, measuring the traffic density, investigating the traffic accidents as well as in pursuing vehicle crimes according to the increasing in number of vehicles. The captured images on the real environment of the CLPR is contaminated not only by snow and rain, illumination changes, but also by the geometrical distortion due to the pose changes between camera and car at the moment of image capturing. We propose homographic transformation and intensity histogram of vertical image projection so as to transform the distorted input to the original image and cluster the character and number, respectively. Especially, in this paper, the Multilayer Perceptron Algorithm(: MLP) in the CLPR is used to not only recognize the charcters and car license plate, but also determine the optimized ratio among the number of input, hidden and output layers by the real experimental result.
 Keywords
Recognition Algorithm;Multilayer Perceptron;Error Back Propagation;Best Recogntion Layer Ratio;
 Language
Korean
 Cited by
 References
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