Research On Image Correction Technique Of Accident Scene Based On Landmark Automatic Detection

In recent years, with the great development of our country’s socio-economy, the usage of automobile is bigger and bigger. While automobile brings great convenience to human, it gives rise to more and more safety problems. Traffic problems not only seriously endanger people’s lives as well as causing great damage of property, but to a certain extent, affect the social harmony, stability and development. In view of the exploration way after the accident scene, the existing measurement is mainly manual reconnaissance, which leads to wasting time too much and influences the process of the accident. Accompanied by subjects such as computer vision technology and image processing technology, digital photogrammetry has been commonly used to accident survey. Compared with manual drawing, digital photography equipment effectively reduces time delay of the exploration and provides great convenience for drawing the accident scene.Along with the increasing usage of ordinary photography device, the limits of traditional method has been causing more attention from accident tester. Selecting image coordination by manual easily causes bigger coordination error, affects the survey precision, and time loss of accident analysis accordingly. What’s more, the camera imaging system, point position and nonlinear distortion factors such as lens distortion, further lead to bigger correction error of vertical view.Based on the above these factors, the essay focuses on two automatic detection means of the image coordinates, which are used to automatically detect the marker image coordinates of the target area, so as to ensure accuracy of survey and save the time of accident image drawing. Later considering the camera radial distortion factors, use improved Tsai two-step camera calibration to optimize the internal and external camera parameters analysis.In order to ensure accuracy of automatic detection, preprocessing operations are taken, mainly including gray level transformation, noise removal and threshold segmentation, so as to distinguish markers from background clearly, and provide theoretical basis for the realization of the automatic detection.This paper mainly introduces two methods of image automatic detection: automatic test based on the projection and the active contour method based on CHAN-VESE. For the first approach, use the method of projection to rough localization of target area at first, and then make accurate positioning of markers by the biggest circulation domain method, and eventually obtain the accurate image coordinates of marker. For the second method, apply template matching method based on gray level to localize target area roughly, and then achieve the precise positioning of markers based on CHAN-VESE method.Two-dimensional geometric correction mode is used for bird-view correction of the interested area. The space coordinates are firstly gotten according to four reference point method, and correction model is set up. And then attaining unknown parameters make preparation for after-test. Considering the camera nonlinear distortion factors, it will have deviation between actual coordinates and the theoretical image coordinates. The checkerboard template is used for nonlinear calibration of internal and external parameters.In order to verify the validity and precision of automatic detection method, make field experiments to detect precision respectively from the height of camera shooting, the horizontal distance of the camera and mutual distance between target area, and make data analysis on whether the ranging precision of reference line is related to the location of the coverage area. Finally, compared with manual selecting image coordinates, the automatic detecting method is verified to be effective.