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Alternative TitleResearch on Image Processing for Visual Control
Thesis Advisor徐德
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword图像处理 视觉检测 视觉控制 路面破损检测 焊缝检测 Image Processing Visual Detection Visual Control Pavement Dilapidation Detection Welding Seam Detection
Abstract本文从视觉控制的角度,研究图像处理问题。本文结合路面破损图像和高噪声焊缝图像,着重对图像处理算法进行了探讨。结合机器人的自主作业,对视觉控制的关键技术进行了简要分析。 1、提出了一种基于马尔可夫模型的路面破损识别方法。将路面图像被分成若干子块,每一个子块都有一个与该处局部裂缝形状对应的状态,状态值中隐含了局部破损形状的信息。这样构造出的马尔可夫模型,可以方便地求出马尔可夫模型的状态概率和状态转移矩阵,用于破损类别的识别。实验结果验证了该方法的有效性。 2、针对具有高干扰噪声的焊缝图像,提出了一种基于子块Radon 变换的边缘检测方法。该方法将焊缝图像分成若干子块,利用焊缝和干扰的先验知识,在子块上检测边缘并利用Radon 变换识别出候选焊缝边缘。然后,利用Hough变换在子块检测出的候选焊缝边缘上提取出焊缝特征。实验给出了与其他算法的比较,并验证了算法的有效性。 3、介绍了视觉伺服系统的构成和分类,分析了图像特征选择、控制算法设计等关键技术。
Other AbstractIn this dissertation, the problem of image processing is studied in the view of visual control. The image processing algorithms are discussed for the pavement distress images and welding seam images with heavy noise. The key technologies are simply analyzed for the autonomous working of robots. 1. A new approach is presented for the problem of pavement dilapidation classification based on Markov Model. In this approach, a picture is partitioned to blocks, and every block has a state with local shape information. Then the state probability and the state transfer probability are computed for classification. The effectiveness of the algorithm is verified by experiments. 2. A new edge detection approach based on Radon transform in sub-areas is designed for welding seam images with noise of severe disturbances. It is divided to many sub-areas for a frame of welding seam image. Edge detector is applied to sub-areas, and candidate welding seam edges in a sub-area is recognized via Radon transform according to the knowledge of the welding seam and the disturbances in advance. Based on the candidate welding seam edges detected from sub-areas, Hough transform is employed to extract the feature lines of the welding seam. The comparison experiments with traditional methods are also provided to illustrate the performances of the proposed method. The experimental results verify the effectiveness of the proposed approach. 3. The configuration and classification of visual servoing systems are introduced. The key technologies such as the selection of image features and the design of control algorithms are simply analyzed.
Other Identifier200528014628018
Document Type学位论文
Recommended Citation
GB/T 7714
王五丰. 视觉控制中的图像处理研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2008.
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