Introduction

Machine vision is a cross-field comprehensive discipline based on light, machinery, electricity, computing and control. Its visual method detection has the advantages of non-contact, fast speed and high accuracy, and is suitable for online industrial product detection. All contents of this experiment refer to real industrial application cases, and can be used as undergraduate experimental teaching courses in optoelectronics, measurement and control, machinery, and automation majors, or as practical training courses for students in related higher vocational majors.

Experiments

a)Machine vision light source system selection experiment

Detection of metal surface details under different lighting methods;

Object contour detection under different lighting methods;

Basic processing such as image binarization, filtering, and edge detection;

Illumination tests at different wavelengths.

b)Lens selection and camera calibration experiments

Ordinary zoom lens calibration experiment;

Telecentric lens calibration experiment;

c)Workpiece measurement experiment

Workpiece length measurement;

Workpiece contour measurement;

Workpiece area measurement.

d)Resolution measurement experiment of optical system

e)Target recognition and tracking experiment

Target rotation, zoom, occlusion and incomplete matching tests;

Experiment on target trajectory drawing and displacement measurement.

f)Color identification experiment

g)OCR text identification experiment

h)QR code recognition experiment

Experimental Knowledge

Camera calibration, resolution measurement, optical system imaging quality, edge extraction, binarization, 2D barcode, OCR, telecentric optical path, pattern recognition, light source lighting technology.

Typical Testing

Target Recognition and Tracking Software            Character Recognition Software

Camera Calibration Software                     Basic Image Processing Software