License Plate Recognition System for Moving Video Streams

• Main Authors: Wei-Shang Chang, 張瑋珊
• Other Authors: Mon-Chau Shie
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/k8spz8

碩士 === 國立臺灣科技大學 === 電子工程系 === 99 === License plate recognition systems have been developed for many years. Most of them are installed with video cameras at fixed locations such as highway toll stations or parking lots. However, very few studies have focused on license plate recognition system with moving camera. In Taiwan, the density of vehicles is ranked top in the world. Taiwan is also known as the highest motorcycle-density country in the world. Presently the police investigating stolen vehicles use system by manually entering license plate numbers to check if they are stolen vehicles or not. In this thesis, we develop a plate license automatic recognition system with moving cameras. This allows polices to record the car or motor-cycle plate numbers while patrolling in their cars. This system comprises the following modules: image pre-processing, license plate localization, plates processing, and optical character recognition. First, pre-processing module is used to converts color input video into 8-bits grayscale images. Next, license plate localization module uses Sobel edge detection operator to find strong vertical texture and locates the license plate area in images. Then, the plate-processing module uses adaptive threshold processing to get more accurate area of license plate. In this module, if the license plate characters are white, they will be transformed into black characters. Finally, optical character recognition module is used to recognize the character. We have adapted the Tesseract-OCR engine to do the task. We use captured plate charter templates to train its characters database and get good recognition result.. Experimental results show that our system has 98.61% successful license plate areas localization rate. It achieves 90.52% successful license plate recognition.