Motion vehicle detection method resisting light effect

Abstract

The present invention discloses a motion vehicle detection method resisting a light effect. The method comprises the following steps: acquiring a video sequence image; extracting a motion region image in the video sequence image by using a frame difference method; analyzing a histogram of the motion region image, determining whether the image is a light unevenness image, and if yes, removing the light effect and then performing background difference processing; eliminating light unevenness of the motion region image by using a homomorphic filtering algorithm; and by using a background difference algorithm, performing motion vehicle detection on the motion region image after removing the light evenness, so as to obtain a detection result. According to the motion vehicle detection method resisting the light effect, the motion region image is extracted by using the frame difference method, and then only the motion region image is processed, so that the subsequent operation amount can be greatly reduced, and operation efficiency can be improved; and filtering is performed by using the homomorphic filtering function, thereby effectively eliminating the light unevenness effect and making the detection result more accurate.

Description

technical field [0001] The invention relates to a moving vehicle detection method resistant to the influence of light, and belongs to the technical field of image processing. Background technique [0002] Moving object detection technology is one of the hotspots and difficulties in the field of video surveillance at home and abroad. Currently commonly used moving target detection methods are: frame difference method, background difference method and optical flow method. The advantage of the inter-frame difference method is that the algorithm is simple to implement and the programming complexity is low; it is not sensitive to scene changes such as light, can adapt to various dynamic environments, and has good stability; but it cannot extract the complete area of ​​​​the object, only out of bounds while depending on the chosen interframe time interval. The background difference method is fast and accurate in detecting moving targets, and the algorithm is simple and easy to i...

AI Technical Summary

Problems solved by technology

The advantage of the inter-frame difference method is that the algorithm is simple to implement and the programming complexity is low; it is not sensitive to scene changes such as light, can adapt to various dynamic environments, and has good stability; but it cannot extract the complete area of ​​​​the object, only out of bounds while depending on the chosen interframe time interval

The background difference method is fast in detecting moving targets, accurate in detection, simple in algorithm, and easy to implement; but usually slow in operation, easily affected by light changes, and poor in removing shadows of targets

The principle of the optical flow method is to assign a velocity vector to each pixel in the image to form an image sports field. At a specific moment of motion, the points on the image correspond to the points on the three-dimensional object one by one. This correspondence can be obtained by The projection relationship is obtained, and according to the velocity vector characteristics of each pixel point, the image can be dynamically analyzed; but for the video surveillance system, the images used are basically captured by the camera in a static state, so there are real-time and accuracy requirements For the system, purely using the optical flow method to detect the target is not practical, and the method has high computational complexity and requires special hardware support, which is not conducive to real-time implementation

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