SIA OpenIR  > 智能产线与系统研究室
Alternative TitleAutomatic Wheel Identify and Classify Based on Computer Vision
Thesis Advisor刘伟军 ; 夏仁波
Keyword轮毂 图像处理 边缘提取 识别分类
Call NumberTP391.41/Y27/2009
Degree Discipline计算机应用技术
Degree Name硕士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Other AbstractWith the increase of global automobile production year by year,the market demand of wheel grows rapidly. The 80% of the domestic automotive wheel is made by the casting,while casting wheel need finishing,by mixed-flow production line together with the wheel hub in their working hours the right type will increase production efficiency. In the past the job of identification the type relied on manual identification, so the workers under greater workload and the speed of production line resulting in visual fatigue, so the misjudgments occur from time to time. Therefore, enterprises need for a wheel hub automatic identification classification system to improve production efficiency. Computer vision is a high-tech for identification the images of the scene, in order to achieve the expansion of human visual function. Take advantage of this technology we can solve lots of the problem in image recognition and detection, replace the outdated manual identification and improve efficiency and identify the level of industrial automation. The wheel automatic identification and classification system based on computer vision consist of several parts: firstly the image acquisition system collects the wheel images from the production line and deals with the picture; then the image preprocessing system includes the image extraction of wheel regions, image denoising, and so on; finally recognition system realizes the structure four one-dimensional non-invariant variable in translational invariance, the proportion of invariance and the range of linear transformation for the characterization of the gray-scale image wheel characteristics, using the Canny edge detection operator cylindrical wheel contour extraction which is followed by a round of external outline the use of improved Hough transform method to calculate the largest diameter wheel, and at last classify the wheel type by the Mahalanobis distance discriminant method. In this paper, the system of wheel automatic identification and classification was designed, the realization of the image acquisition, image processing and recognition, such as wheel basic functions of models to overcome the traditional disadvantages of artificial recognition to adapt to the rapid identification of mixed-flow production line classification needs, carried out for the model of the computer vision system to identify the study of modern industrial production for the realization of a new type of image recognition technology has made some attempts and discussion.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
杨飞. 基于计算机视觉的轮毂自动识别与分类[D]. 沈阳. 中国科学院沈阳自动化研究所,2009.
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