An Effective Method for the Recognition and Verification of Bangladeshi Vehicle Digital Number Plates

Abstract

In this study, an effective and automatic technique has been proposed to detect, recognize and verify Bangladeshi number plates. There are four steps in the proposed method: Pre-processing, extraction and segmentation, recognition and verification of the number plate. Image contrast-enhancing and tilt correction techniques are used in the proposed method. Different techniques like edge detection, morphological operations, bounding box method and connected component analysis are used for the extraction and segmentation of number plates and their characters. The template matching method is used for recognizing the characters. The authentication and verification process for a vehicle is the distinctive feature of the proposed method. We have developed a dataset of 500 Bangladeshi number plate images for our research. A rich template dataset and a cloud database containing vehicle details have also been developed for number plate character recognition and vehicle verification purposes, respectively. The proposed method achieves detection, extraction, segmentation and recognition accuracies of 96.8, 94.8, 98.3 and 97.6%, respectively. It is observed that the proposed technique outperformed many other existing techniques.