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Super resolution based low cost vision system

机译:基于超分辨率的低成本视觉系统

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摘要

Machine vision (MV) is the technology which provides camera based analysis of images for various applications such as automatic quality inspection, pattern recognition, process flow control and pattern classification. The machine vision system is expensive as it contains high resolution camera and lenses. The paper proposes an algorithm to develop a low cost web camera based vision system for screw thread inspection. The Bayesian super-resolution method is used to super-resolute the images captured using low resolution web cameras. The parameters such as major, minor and pitch diameters, depth and thread angles are measured by using the proposed dimension measurement method. The results of web camera based automatic inspection of major diameter, minor diameter, pitch diameter, thread and depth of hex lag screw thread shows an error of range 0.000 to 0.310 mm. The comprehensive experimental results reveal that the proposed approach is suitable for real-time high speed quality analysis in various industries.
机译:机器视觉(MV)是为各种应用提供基于相机的图像的技术,例如自动质量检查,模式识别,过程流量控制和模式分类。机器视觉系统很贵,因为它包含高分辨率相机和镜头。本文提出了一种算法,用于开发基于低成本的基于Web摄像头的视觉系统,用于螺纹检查。贝叶斯超分辨率方法用于超固化使用低分辨率网相机捕获的图像。通过使用所提出的尺寸测量方法测量诸如主要,次要和间距直径,深度和螺纹角的参数。基于网络摄像机的主要直径,小直径,俯仰直径,螺纹和深度的六角滞螺纹的螺纹的结果显示出误差范围为0.000至0.310毫米。综合实验结果表明,该方法适用于各行业的实时高速质量分析。

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