ACCURACY IMPROVEMENT OF A PROVINCE NAME RECOGNITION ON THAI LICENSE PLATE

摘要

License plate recognition is mechanism for extracting information on a license plate and converting to an encoded text. The information on license plate is letters, number, and province's name. Although, the license plate recognition for Thai has been introduced for more than ten years, it has a low accuracy rate in the province part. This is due to a low resolution of the province, which has approximately 15-18 pixels of the height. This research aims to improve the accuracy of the province name recognition on Thai license plate. The experiments are conducted on images that were captured from the South of Thailand. A two step classification is proposed to improve accuracy. Given an image of a province's part, it is classified according to the length of the name. Then, the HOG feature is extracted for predicting the province's name using a classifier. The proposed method achieve 90% accuracy, which is higher than classifying using only Extreme Learning Machine and Decision Tree.