Color license plate positioning method

Abstract

The invention belongs to the field of automatic license plate recognition and application of intelligent video monitoring, and relates to a color license plate positioning method. The method comprises the following steps of: acquiring CIELab color space automobile images; normalizing the images; performing morphological expansion processing on four classes of binary images by using diamond structure elements; obtaining a blue-white edge binary image, and obtaining a yellow-black edge binary image; performing expansion processing on the two edge binary images by using horizontal strip structure elements, and marking each potential license plate region; and setting four constraint conditions, namely constraint of license plate region area, relative size constraint of width and height of a license plate and width and height of an image, width-to-height ratio constraint of the license plate and shape constraint of the license plate, recognizing each potential license plate region and extracting the license plate region. The invention has the advantages that: the method is low in calculation quantity and high in processing speed, and is not affected by the interference region and the illumination condition change.

Description

Technical field [0001] The invention belongs to the application field of automatic license plate recognition of intelligent video monitoring, and in particular relates to a license plate positioning method directly aimed at color images. Background technique [0002] Vehicle License Plate Recognition (LPR for short) technology is an important part of the intelligent transportation system. It is widely used in video surveillance fields such as unmanned parking lot, non-parking toll collection and traffic flow control. The LPR system based on computer vision is mainly composed of three parts [1]: license plate location, license plate character segmentation and character recognition. Among them, the license plate location is a key issue of the LPR system, which realizes the judgment of the position of the license plate area in the image. [0003] Domestic research on license plate positioning began in the 1990s and has roughly experienced three stages of development. Early r...

AI Technical Summary

Problems solved by technology

This type of method is simple to implement, fast in processing speed, insensitive to changes in lighting conditions, and has good positioning performance for license plate tilt and deformation. The disadvantage is that there are many false detections.

This kind of method comprehensively considers the color and edge features of the license plate, which can reduce false detections. The disadvantage is that the color of the license plate is easily affected by changes in lighting conditions, and there are many missed detections.

[0004] To sum up, the existing license plate location technology mainly uses the edge features of the license plate to locate the license plate area, and the color information usually only plays an auxiliary role.

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