Application Research on Image Processing in Vehicle Course

Application Research on Image Processing in Vehicle Course Angle Detecting System Chu-qi SU Du-que ZHANG Li-bo HUANG Automotive Engineering Institute Wuhan University of Technology Wuhan, Hubei, China e-mail: [email protected] Abstract — Course deviation of vehicle during running will bring about traffic accidents, and many factors such as the assembling and processing quality of suspension system and steering system will lead to vehicle course angle deviation. For an in-depth study of vehicle course angle deviation, an online automatic detecting method was worked out, which can control a CCD camera to grab images by a photoelectric switch and apply image processing technique to extract key points to calculate the amount of course angle deviation. Keywords- Vehicle course angle; CCD; image processing I. INTRODUCTION Vehicle course angle deviation is a phenomenon that when a normal vehicle is running on a straight line, the driver leaves the steering wheel at the central position freely, but the driving direction always has an inerratic rightward or leftward deviation from vehicle’s longitudinal axis. Vehicle straight deviation is a common fault during vehicle’s running. When it occurs, the driver needs to apply a correction force on the steering wheel all the time, which will increase driver’s operating difficulty and fatigue. Driving deviation will not only bring hard steering but also cause brake bias, which will lead to braking sideslip. Owing to many factors existing in vehicle production, such as the assembling adjustment, the process quality of parts and the road condition, it is impossible to produce a vehicle without any deviation. To keep a good impression of the quality of their products, many car manufacturers define strict limitation standards for straight deviation so as to guarantee a long-term steady qu ality level. However, there is no systematic research on vehicle straight deviation in Chin. What we have is just a certain manual method of determination measurement for some special purposed vehicles (such as paver), which is low-efficient. Based on a high-speed industrial CCD camera, this paper aims at constructing a set of measurement system by applying image processing technique, which can record vehicle course angle deviation real-timely. II. STRUCTURE AND PRINCIPLE OF DETECTION SYSTEM Fig.1 shows the hardware structure of a course angle detection system. S is the emitter pole and R is acceptation pole of opposite-type photoelectric switch. Trigger signal is generated when the vehicle passes by, which will be transmitted to the industrial computer by R; the industrial computer receives the trigger signal and then transmits a control signal to the camera to operate it. If the camera’s shooting speed is not fast enough, trailing smear will appear in the images collected, which will affect image processing and measuring accuracy. Therefore, the camera must be a high-speed industrial CCD camera whose frame rate should reach 500FPS in 1280 × 1024 resolution to ensure shooting speed at the rate of 400f / s. This camera should be installed on the gantry.The industrial computer receives the images which the CCD camera transmits and processes them to obtain the amount of deviation. III. IMAGE PROCESSING TECHNIQUE A. Background Subtraction The first step of image processing is separating the image of vehicle from the background. Background subtraction is used in this paper. The key point of background subtraction is the timeliness of background. As the background changed timely, it is necessary to update the background of detection line timely. Two photoelectric switches are installed on every gantry. When the vehicle passes S10 (S20, S30), the CCD camera begins to take background picture (as shown in Fig. 2); and when the vehicle passes S11 (S21, S31), the CCD camera begins to take vehicle picture (as shown in Fig. 3). By making a subtraction between these two images, we can get a good separating image of the vehicle (as shown in Fig. 4). B. Threshold Segmentation There are some images of rays or other appendages in the vehicle image (such as rays and antenna shown in Fig. 4) after background subtraction. Threshold value setting can eliminate the effect for the subsequent image processing. Since the shape of image gray scale histogram is volatile, it sometimes contains double peaks without obvious trough or appears without obvious peaks and trough. And it is always difficult to determine the area ratio between two regions. Under the circumstances, the maximum variance automatic shareholding method [1] will be used to get a satisfactory result. 2009 Second International Conference on Information and Computing Science 978-0-7695-3 634-7/09 $25.00 © 2009 IEEE DOI 10.1109/ICIC.2009.1 44 140 2009 Second International Conference on Information and Computing Science 978-0-7695-3 634-7/09 $25.00 © 2009 IEEE DOI 10.1109/ICIC.2009.1 44 140 Authorized licensed use limited to: D Muhammad Noorul Mubarak. Downloaded on July 20,2010 at 08:32:51 UTC from IEEE Xplore. Restrictions apply.

Application Research on Image Processing in Vehicle Course

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