License plate detection and recognition algorithm for vehicle black box

• Published in: 2017 International Automatic Control Conference (CACS) pp. 1 - 6
• Main Authors: Kim, Jung-Hwan, Kim, Sun-Kyu, Lee, Sang-Hyuk, Lee, Tae-Min, Lim, Joonhong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2017
• Subjects: Classification algorithms; Distortion; Image edge detection; Image Processing; k - nearest neighbor; License plate; License plate recognition; Support vector machine; Support vector machines; Vehicle Black Box
• DOI: 10.1109/CACS.2017.8284273

Almost every vehicle has currently installed black box since the stored images by black box can be used to investigate the exact cause of the accident. One of the most important aspects in an accident investigation is the license plate detection and recognition as the license plate has information about the driver and car. This paper presents a novel algorithm for license plate detection and recognition using black box image. The proposed license plate recognition system is divided into three stages: license plate detection, individual number and character extraction, and number and character recognition. The Gaussian blur filter is used to remove noise in the image and then we detect the license plate edge using modified Canny algorithm. Second, we determine license plate candidate image using morphology and support vector machine. Finally, we recognize the numbers and characters using k-nearest neighbor classifier. The experimental study results indicate that the license plate detection and recognition algorithm has been successfully implemented.