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A Method for Segmenting and Recognizing a Vehicle Licence Plate from a Road Image

To solve the problems of heavy traffic, due to the increase in the number of vehicles, modern cities need to establish effectively automatic systems for traffic monitoring and management. One of the most useful systems is the License-Plate Recognition System which captures images of vehicles and reads the plate’s registration numbers automatically. Our method in this paper presents a robust algorithm for segmenting and recognizing a vehicle license plate area from a road image. As preprocessing steps, we statistically analyze the features of some sample plate images, and compute thresholds for each feature to decide whether a pixel is inside a plate or we cannot decide it. Our methodology starts from constructing the binary version of a road image according to the thresholds. Then, we select at most three strong candidate areas by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. Our algorithm is stable and robust against the cases of plate transformation and/or decolorization. The experimental results show 98.05% of successful plate recognition for 256 input images.