Lane guide arrow identification method in intersection monitoring environment

Abstract

The invention discloses a lane guide arrow identification method in an intersection monitoring environment, belongs to the field of computer vision, and relates to image processing related knowledge.The method comprises the steps: acquiring a traffic video image sequence based on an intersection monitoring camera; establishing a lane background model by using a background modeling technology; detecting a lane line by utilizing Hough transform on the basis of the established lane background model, taking an end point of the detected lane line as an original coordinate point of image perspective transformation, and finishing perspective transformation in combination with a least square method to obtain a lane top view, so as to correct perspective deformation generated by shooting of a camera; then, respectively projecting the lane top view in the vertical direction and the horizontal direction, and carrying out screening segmentation according to the ratio of the length of a standard guide arrow to the width of the lane to obtain all target area images only containing a single guide arrow; finally, performing similarity matching on the guide arrows obtained through segmentation anda standard guide arrow template one by one, and recognizing the types of the guide arrows of all lanes.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to a lane guiding arrow recognition method in a crossing monitoring environment. Background technique [0002] Traffic signs such as directional arrows contain important road information, and their intelligent recognition is of great significance for the construction of intelligent transportation systems. With the continuous development of intelligent transportation systems, the identification of road surface information has also aroused extensive research interests of scholars, especially in the field of assisted driving, many researchers have achieved extensive research results; on the other hand, road monitoring environment The following road sign information recognition will be of great value to the realization of a more intelligent traffic control system, and it is an important basis for realizing intelligent traffic control functions such as intelligent road informat...

AI Technical Summary

Problems solved by technology

However, there are still relatively few studies on road surface information recognition in the surveillance environment. In addition, due to the complex road environment, problems such as vehicle occlusion, road surface impurities, illumination changes, shadows, and perspective deformation generated by surveillance cameras are of great concern to guide arrows, etc. The recognition of road sign information produces more interference, which seriously affects the accuracy and robustness of recognition, and generally has the problem of low efficiency

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