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The Vehicle License Plate Identification in License Plate Sorting

Author: FuZuoJie
Tutor: PengYanJun
School: Shandong University of Science and Technology
Course: Applied Computer Technology
Keywords: license plate recognition Lab license plate localization character segmentation character recognition
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 9
Quote: 0
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Abstract


With the development of intelligent transportation, license plate recognition applications more widely, the automated sorting system has also joined the license plate license plate recognition technology. The current license plate recognition are generally obtained from the intersection traffic control system in the image into a grayscale image after processing. Recognition algorithms often have to consider the background, weather, licenses, and many other objective factors tilt the impact of high complexity do not have the engineering conditions. The license plate license plate sorting process for comparing a single image background, the light more evenly. License plate images of such rapid and accurate identification method has important applicationsThis paper studies the license plate location algorithm which commonly be used. This paper puts forward a kind of using color information and projection combination of license plate localization method. According to the characteristics of the common sort license plate, the method bases on the Lab color gamut space theory. With the vehicle images of the space in the Lab color gamut color features, use the mathematical morphology of inflation, corrosion and the image segmentation.Use the feature extraction based on character and template matching method of identification. Using the.Net and SQL2000 Server database, we developed a license plate recognition system and automatic sorting system. was analyzed. At the end we analyzed the effect of the system.This sorting algorithm in license plate system has been applied. Experiments show that the algorithm in the image of the location of the license, not the color of the license restrictions on the license changes in tilt and image contrast has strong adaptability. System test results, license positioning accuracy rate of 94.8%,84.5% character recognition rate is a result, the user was satisfied.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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