基于机器视觉缺陷检测的实践教学平台研究

Research on the construction of practice teaching platform based on machine vision defect detection

目的构建一个能够模拟工业现实环境的机器视觉缺陷检测软件平台,用于工业自动化和计算机图像学的教学工作,便于学生掌握工业机器视觉系统的基本原理及处理流程,掌握数字图像的各种算法及其应用场景。方法在对机器视觉缺陷检测系统需求进行分析的基础上,使用Python 2.75和Opencv 2.4构建系统的软件模块。结果与结论该平台能够实现相机配制、图像获取、图像标定、图像处理、分析统计等工业缺陷检测全过程,并将计算机图像的相关理论教学融于实践教学过程,对于提高学生课堂的互动性、激发学习兴趣、掌握各种图像处理算法有着重要意义。

Purposes-To construct a machine vision defect detection software platform, which is capable of simulating the real industrial environment artd used in the teaching of industrial automation and computer graphics, so that students can master the basic principle and processing flow of industrial machine vision system as well as various algorithms and application scenes of digital images. Methods-Python 2.75 and Opencv 2.4 were used to build of analyzing the requirements of machine vision defect the software modules of the system on the basis detection system. Results and Conclusions-The software platform can realize the whole process of industrial defect detection such as camera preparation, image acquisition, image calibration, image processing, analysis and statistics. And such the in- tegration of the theory teaching of computer images into practice teaching is of great significance to the improvement of students＂ interactivity in class, their inspiration for learning and mastering various image processing algorithms.