VEHICLE LICENSE PLATE READING USING MATLAB

Electronics & Telecommunication Engineering

We propose a camera-based assistive text reading framework to read characters and numbers from number plates of vehicles in daily use. To isolate the object from cluttered backgrounds or other surrounding objects in the camera view, we first propose an efficient and effective motion- based method to define a region of interest (ROI) in the video. This method extracts moving object region by a mixture-of-Gaussians-based background sub- traction method. In the extracted ROI, number plate localization and recognition are conducted to acquire information. To automatically localize the number plate regions from the object ROI, we propose a novel number plate localization algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized number plate regions are then binarized and recognized by off-the-shelf optical character recognition software. The recognized text codes are output to users. Performance of the proposed text localization algorithm is quantitatively evaluated on ICDAR-2003 and ICDAR-2011 Robust Reading Datasets. Experimental results demonstrate that our algorithm achieves the state of the arts. The proof-of-concept prototype is also evaluated on a dataset collected to evaluate the effectiveness of the system’s hardware. We explore user inter- face issues and assess robustness of the algorithm in extracting and reading text from different objects with complex backgrounds

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