Night vehicle license plate positioning method based on maximally stable extremal region (MESR) and stroke width transformation (SWT) combination

Abstract

The present invention relates to a night vehicle license plate positioning method based on MESR and SWT combination, and provides a novel license plate positioning method based on the MESR and SWT combination aiming at the problem that a conventional license plate positioning method can not position the license plates effectively on a night poor illumination condition or due to the vehicle speed influence. The method comprises the steps of after the contrast ratio of an original image is enhanced, carrying out the Canny edge detection and the MSER extraction, segmenting the MSER by the edge expansion and screening the segmented MSER according to the license plate character geometrical characteristics; then carrying out the SWT based on the morphological processing in the screened region; finally, aggregating a candidate region, and combining the license plate geometrical characteristics to finish the fine positioning of the license plates. By the test verification, the method is high in positioning accuracy, can position the license plates accurately on different scenes and different illumination conditions in the daytime, at the same time, can position the night low-resolution license plates effectively, and has much higher positioning accuracy and robustness than other conventional license plate positioning methods on a low-resolution condition.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition and image processing, and in particular relates to a vehicle license plate positioning method at night. Background technique [0002] License plate recognition is an important part of the intelligent transportation system. The quality of license plate positioning directly affects the accuracy of license plate recognition, which is a key step in the process of license plate recognition. Therefore, license plate location has always been a research hotspot at home and abroad, and researchers have proposed many related algorithms. Among them, license plate location is mainly based on texture features, color features, edge information, transform domain analysis and morphological processing, etc., combined with license plate features. In recent years, many researchers have continuously improved and integrated traditional algorithms, and some researchers have applied new algorithms to licens...

AI Technical Summary

Problems solved by technology

[0003] Although the Boris Epshtein stroke width algorithm applies the stability of stroke width and can effectively locate text under certain conditions, it still has the following disadvantages: ① It is necessary to calculate the gradient of each pixel, and then find edge points along the gradient direction or the opposite direction Yes, the algorithm takes a long time; ②Determine the stroke width based on the edge pixel point pairs, relying on the character edge and the integrity of the character strokes. If the character edges are blurred or the strokes are incomplete, it will cause false deletion of the candidate area.

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