Enhancement of Vehicle License Plate Images by Temporal Filtering

Optical Character recognition is used widely as a tool in intelligent transportation systems for recognition of the car license plate from a still image or video. The accuracy of Optical Character Recognition partially depends on the quality of the input image. In this study, a set of simple and efficient methods are proposed to improve the quality of the car license plate image extracted from video clips to reduce the error rate for the license plate OCR even at low resolutions. Mean, median, and maximum filters are commonly used algorithms to filter noise and enhance an image. The proposed technique by Dr. Bodur extends them to time domain by including the pixels of the consequent images of the video clip in filtering algorithm. The OCR error rate is tested on fifty road and street video clips by decreasing the resolution of the images and filtering them with common and proposed filtering methods. The test results indicate that all proposed methods, improve the accuracy of OCR, and the highest reduction of error is obtained by the proposed temporal maximum filtering method. Keywords: License Plate Recognition, temporal image enhancement, Vehicle Plate OCR.