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http://dx.doi.org/10.3745/KTSDE.2014.3.9.361

Real-Time Vehicle License Plate Recognition System Using Adaptive Heuristic Segmentation Algorithm  

Jin, Moon Yong (현대모비스 연구개발본부)
Park, Jong Bin (전북대학교 전자정보공학부)
Lee, Dong Suk (전북대학교 전자정보공학부)
Park, Dong Sun (전북대학교 전자공학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.3, no.9, 2014 , pp. 361-368 More about this Journal
Abstract
The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.
Keywords
License Plate Recognition(LPR); Heuristic Segmentation; AdaBoost; Histogram of Oriented Gradients(HOG);
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Times Cited By KSCI : 1  (Citation Analysis)
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