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A Vehicle License Plate Recognition Using the Haar-like Feature and CLNF Algorithm  

Park, SeungHyun (홍익대학교 대학원 전기정보제어공학과)
Cho, Seongwon (홍익대학교 전자전기공학부)
Publication Information
Smart Media Journal / v.5, no.1, 2016 , pp. 15-23 More about this Journal
Abstract
This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.
Keywords
License Plate Recognition; AdaBoost; License Plate Detection; Character Detection; Character Recognition;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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