摘要 :
Traditional methods of license character extraction cannot meet the requirements of recognition accuracy and speed rendered by the video vehicular detection system.Therefore, a license plate localization method based on multi-scal...
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Traditional methods of license character extraction cannot meet the requirements of recognition accuracy and speed rendered by the video vehicular detection system.Therefore, a license plate localization method based on multi-scale edge detection and a character segmentation algorithm based on Markov random field model is presented.Results of experiments demonstrate that the method yields more accurate license character extraction in contrast to traditional localization method based on edge detection by difference operator and character segmentation based on threshold.The accuracy increases from 90% to 94% under preferable illumination, while under poor condition, it increases more than 5%.When the two improved algorithms are used, the accuracy and speed of automatic license recognition meet the system's requirement even under the noisy circumstance or uneven illumination.
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摘要 :
In this paper, a kind of practical image segmentation algorithm for segment characters from car license plate is presented, based on morphology and labeling. First, by morphological operation, noise in the binary image of license ...
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In this paper, a kind of practical image segmentation algorithm for segment characters from car license plate is presented, based on morphology and labeling. First, by morphological operation, noise in the binary image of license plate can be greatly decreased. Then, by labeling, each connected pixel component is given a unique label. Finally, by the known data of license plate, each character is extracted correctly. The advantage of this method is that it can deal with plates with different sizes and connected characters plates, and inclined plates. The experiment results show that it is an effective way to extract characters from the license plate, and can be put into practical use.
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