基于坐标和图像技术的三维表面特征区域的检测
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摘要
表面质量是衡量产品质量、评价使用过程中运行状况的重要指标之一，目前生产和科研部门对三维曲面上的表面检测需求越来越大，而且存在许多难点。本论文将坐标测量和图像检测技术进行有机结合，研究了曲面上具有某种特征的特征区域非接触、高精度、自动的测量方法，精心设计了测量系统的每个环节，提出了新的原理与方法。
在总结和分析各种表面检测的基础上，提出了表面特征区域的概念和表征方法，有利于规范检测条件、手段和评定方法。探讨了基准面的确定方法、检测规范制定的原则及内容，对表面特征区域的定量测量具有实用的参考价值。
提出了一种图像坐标测量的新方法，适用于三维表面信息的自动扫描测量。此方法采用信息融合、非正交坐标测量和机器人等新技术，将接触测量和非接触测量、粗定位和精测量、坐标测量和图像检测相结合。总结了软硬件系统的设计原则，建立了完整的数据处理基础理论；根据测量系统的特点自行设计了标准样件，并开发了一种简便实用的摄像机部分参数的标定方法；阐明了利用计算机图形学的投影概念、实测的几何尺寸等重构表面信息的关键技术。详细讨论了表面特征区域的图像采集、识别、坐标变换、表征、数据处理等内容，给出了扫描测量中误差分析和评定方法。另外借助于δ_5判据，能即时判断图像获取质量、阈值选取的合理性。并成功地应用到两个实际工程中，证明了该方法的可行性和实用性。实验表明这种测量方法精度较高、效率高、可靠性高、通用性强。
用现代信息处理的理论，增强了图像处理能力。成功地将自组织特征映射(SOFM)神经元网络和误差逆传播(BP)神经元网络相结合用于彩色图像的分割，提高了目标区域识别的准确性。
提出了ESSA(EMD Search and Snakes Approach)方法，将经验模式分解(EMD)和Snakes模型相结合，采用改型EMD将特征区域从复杂背景下分离出来，然后在特征区域附近用向心搜索法缩小检测区域，最后用Snakes模型迭代逼近特征区域边缘，达到了复杂背景下检测复杂目标的目的。
针对具有镜面反射特性的光滑球面，提出了一种利用漫反射带的镜像变形对表面缺陷进行快速检测的新方法。这种方法克服了背景噪声在图像处理中会造成较大误差的缺点，使缺陷的凹凸和大小等特征的分析更容易。
Surface measurement is an important criterion to judge product quality and evaluate status in use. Now manufactory and scientific research are exigent of surface measurement on 3D surface in which there are many difficulties. A non-contact, high accuracy and automatic method combining coordinate measuring technique with digital image technique was introduced to measure feature region on curved surface. New principle and methods were proposed.
Analyzing and generalizing various surface measurement methods, concept and representations of surface feature region are presented in favor of standardization at measurement condition, means and evaluation. The determine method of datum plane as well as regulation and items about measurement standard establishment was discussed. They were very practical for quantificational mensuration of surface feature region.
A new image-coordinate measurement is presented for automatic scan measurement of 3D surface. The method adopted new techniques such as information fusion, non-orthogonal coordinate measuring and measuring robot. And it combined contact measurement with non-contact measurement, rough orientation with precise measurement as well as coordinate measurement with digital image technique. The design principle of software and hardware was summarized. Full basic theory of data processing was established. According to system characteristic, a plane glass templet was designed and a simple calibration method of camera partial parameter was developed. The key technique of restoring surface information using projection
concept in computer graphics and measuring dimensions was expatiated. The image capture, extraction, coordinate transform, representation and data processing for surface feature region were discussed in detail. Error analysis and evaluations at scan-measure were given. In addition, with the aid ofδ_5 criterion, quality of image capture and rationality of threshold selection can estimate quickly. And then two engineering applications show that this method is feasibility and practicability. Practical tests show that this is high effective, accurate, reliable and universal method.
Image processing capability was enhancive by modem information processing theory. A method combining self-organizing feature map (SOFM) neural network and error back-propagation training (BP) neural network was used to segment color image more accurately in favor of improving accuracy for object region extraction.
ESSA (EMD Search and Snakes Approach) method combining empirical mode decom-position (EMD) with Snakes model was presented. Firstly, feature region was separated from complicated background by remodel EMD. And then, detection region was farther reduced by towards-center search method at feature region around. Finally, feature region edge was detected by iterative approach based on Snakes model. In this way the purpose of complicated object extraction from complicated background was achieved.
To detect defects on smooth hemispherical shell surface with specular reflection, a novel fast method according to distortion image of reflection strip was proposed. This method overcomes disadvantage of considerable errors caused by background noise during image processing and is easy to analyze the defect features such as size, concave and convex.
在总结和分析各种表面检测的基础上，提出了表面特征区域的概念和表征方法，有利于规范检测条件、手段和评定方法。探讨了基准面的确定方法、检测规范制定的原则及内容，对表面特征区域的定量测量具有实用的参考价值。
提出了一种图像坐标测量的新方法，适用于三维表面信息的自动扫描测量。此方法采用信息融合、非正交坐标测量和机器人等新技术，将接触测量和非接触测量、粗定位和精测量、坐标测量和图像检测相结合。总结了软硬件系统的设计原则，建立了完整的数据处理基础理论；根据测量系统的特点自行设计了标准样件，并开发了一种简便实用的摄像机部分参数的标定方法；阐明了利用计算机图形学的投影概念、实测的几何尺寸等重构表面信息的关键技术。详细讨论了表面特征区域的图像采集、识别、坐标变换、表征、数据处理等内容，给出了扫描测量中误差分析和评定方法。另外借助于δ_5判据，能即时判断图像获取质量、阈值选取的合理性。并成功地应用到两个实际工程中，证明了该方法的可行性和实用性。实验表明这种测量方法精度较高、效率高、可靠性高、通用性强。
用现代信息处理的理论，增强了图像处理能力。成功地将自组织特征映射(SOFM)神经元网络和误差逆传播(BP)神经元网络相结合用于彩色图像的分割，提高了目标区域识别的准确性。
提出了ESSA(EMD Search and Snakes Approach)方法，将经验模式分解(EMD)和Snakes模型相结合，采用改型EMD将特征区域从复杂背景下分离出来，然后在特征区域附近用向心搜索法缩小检测区域，最后用Snakes模型迭代逼近特征区域边缘，达到了复杂背景下检测复杂目标的目的。
针对具有镜面反射特性的光滑球面，提出了一种利用漫反射带的镜像变形对表面缺陷进行快速检测的新方法。这种方法克服了背景噪声在图像处理中会造成较大误差的缺点，使缺陷的凹凸和大小等特征的分析更容易。
Surface measurement is an important criterion to judge product quality and evaluate status in use. Now manufactory and scientific research are exigent of surface measurement on 3D surface in which there are many difficulties. A non-contact, high accuracy and automatic method combining coordinate measuring technique with digital image technique was introduced to measure feature region on curved surface. New principle and methods were proposed.
Analyzing and generalizing various surface measurement methods, concept and representations of surface feature region are presented in favor of standardization at measurement condition, means and evaluation. The determine method of datum plane as well as regulation and items about measurement standard establishment was discussed. They were very practical for quantificational mensuration of surface feature region.
A new image-coordinate measurement is presented for automatic scan measurement of 3D surface. The method adopted new techniques such as information fusion, non-orthogonal coordinate measuring and measuring robot. And it combined contact measurement with non-contact measurement, rough orientation with precise measurement as well as coordinate measurement with digital image technique. The design principle of software and hardware was summarized. Full basic theory of data processing was established. According to system characteristic, a plane glass templet was designed and a simple calibration method of camera partial parameter was developed. The key technique of restoring surface information using projection
concept in computer graphics and measuring dimensions was expatiated. The image capture, extraction, coordinate transform, representation and data processing for surface feature region were discussed in detail. Error analysis and evaluations at scan-measure were given. In addition, with the aid ofδ_5 criterion, quality of image capture and rationality of threshold selection can estimate quickly. And then two engineering applications show that this method is feasibility and practicability. Practical tests show that this is high effective, accurate, reliable and universal method.
Image processing capability was enhancive by modem information processing theory. A method combining self-organizing feature map (SOFM) neural network and error back-propagation training (BP) neural network was used to segment color image more accurately in favor of improving accuracy for object region extraction.
ESSA (EMD Search and Snakes Approach) method combining empirical mode decom-position (EMD) with Snakes model was presented. Firstly, feature region was separated from complicated background by remodel EMD. And then, detection region was farther reduced by towards-center search method at feature region around. Finally, feature region edge was detected by iterative approach based on Snakes model. In this way the purpose of complicated object extraction from complicated background was achieved.
To detect defects on smooth hemispherical shell surface with specular reflection, a novel fast method according to distortion image of reflection strip was proposed. This method overcomes disadvantage of considerable errors caused by background noise during image processing and is easy to analyze the defect features such as size, concave and convex.
引文
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