Embedded Real-Time Multiple Vehicle License Plate Recognition System

• Main Authors: Chih-Wen Lee, 李志文
• Other Authors: Mon-Chau Shie
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/79815883470750175111

碩士 === 國立臺灣科技大學 === 電子工程系 === 96 === In Taiwan, density of vehicles is come out top in the world. However, it is short of embedded recognition system for license plates of cars and motorcycles in domestic study. In this paper, we proposed a DSP-less embedded system of Real-Time multi-target recognition without professional video camera to solve license plate images in conditions of low-contrast, blur, or skew. The system is composed of three modules: localization, processing of vehicle plates, and character recognition. For the unclear vehicle plate images, we proposed a method which is suitable to binarize the license plate. Compared with localized Otsu’s method of 3 × 3 block processing, our method achieved 24.39% improvement for cars’ license plates recognition accuracy, and 25.56% improvement for motorcycles’ license plates. To improve template matching, we separated the character templates into some subsets by character’s outline, and could effectively avoid miss-recognition of the characters 6, 9, S. Moreover, by calculating the ratio of left and right side’s background pixels of character’s contour, the characters 0, D, 8, B could be authentically recognized. The experimental videos were captured upon a sky bridge on Roosevelt Road, Taipei. The accuracies of car’s and motorcycle’s license plate recognition are 82.92% and 80.85%, and the accuracy of localization is 96%. The performance on embedded system (XScale-PXA270 624 MHz / Linux) is 7~8 fps.