An efficient method for extraction and recognition of bangla characters from vehicle license plates

Abstract

Recognition of characters from vehicle license plate plays a vital role in vehicle tracking, controlling, and maintaining traffic on the roads and high ways. This paper presents an automatic system to detect plate area and recognize characters. The research is carried out on Bangladeshi vehicle license plates because this is a demandable research area in the present age. The method has been implemented using the five consecutive steps such as license plate detection, extraction, character localization, extraction of characters, and recognition of extracted characters. We have introduced an algorithm to detect the Region of Interest (ROI) from the input image. It is performed by applying morphological operation and histogram analysis of vertical and horizontal projection profiles. A dynamic threshold is used to filter out both horizontal and vertical histogram values and ROI is extracted from the license plate image using different geometric properties such as area, bounding box, and aspect ratio. Character segmentation is performed by applying the method of connected component analysis and bounding box technology. Finally, character recognition is carried out using Support Vector Machine (SVM) classifier where extracted Histogram of Oriented Gradient (HOG) features are used as input. The proposed algorithm is applied to 630 images of license plates of different categories of vehicles and achieved 91% accuracy in the extraction of ROI and 94.6% accuracy in the extraction of characters. We have also achieved 100% accuracy in recognition of Bangla characters from a total of 4725 Bangla characters extracted from 630 images of license plates.