Introduction to machine vision (Chapter 1)

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第 1 页

Chapter 1. Introduction to machine vision 1. Introduction 2. Basic elements of machine vision system 3. Classification 4. Technical specifications 5. Designing a Machine Vision System 2

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1. Introduction ❖Definition ➢Machine vision (MV) is the technology and methods used to provide imaging- based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. ➢Machine vision is a term encompassing a large number of technologies, software and hardware products, integrated systems, actions, methods and expertise. ➢Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science. ➢It attempts to integrate existing technologies in new ways and apply them to solve real world problems. 3

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1. Introduction ❖Definition ➢The overall machine vision process includes planning the details of the requirements and project, and then creating a solution. During run-time, the process starts with imaging, followed by automated analysis of the image and extraction of the required information. 4

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Chapter 1. Introduction to machine vision 1. Introduction 2. Basic elements of machine vision system 3. Classification 4. Technical specifications 5. Designing a Machine Vision System 11

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2. Basic elements of machine vision system 2.1. Overview 2.2. Illumination 2.3. Imaging 2.4. Image processing and analysis 12

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2. Basic elements of machine vision system ❑ 2.1. Overview http://www.digikey.com/en/articles/techzone/2012/jan/versatile-leds-drive-machine-vision-in-automated-manufacture 13

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2. Basic elements of machine vision system ❑ 2.1. Overview OK NG How to automatically detect the defect? 14

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2. Basic elements of machine vision system ❑ 2.1. Overview ❖Illumination ➢Illumination: is the way an object is lit up and lighting is the actual lamp that generates the illumination. ❖Imaging (Camera and lens) ➢The term imaging defines the act of creating an image. 15

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2. Basic elements of machine vision system ❑ 2.1. Overview ❖Image processing and analysis ➢This is where the desired features are extracted automatically by algorithms and conclusions are drawn. ➢A feature is the general term for information in an image, for example a dimension or a pattern. ➢Algorithms are also referred to as tools or functions. 16

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2. Basic elements of machine vision system 2.1. Overview 2.2. Illumination 2.3. Imaging 2.4. Image processing and analysis 17

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2. Basic elements of machine vision system ❑ 2.2. Illumination ❖The goal of lighting in machine vision is to obtain a robust application by: ➢Enhancing the features to be inspected. ➢Assuring high repeatability in image quality. SICK IVP, “Machine Vision Introduction,” 2006. 18

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2. Basic elements of machine vision system ❑ 2.2. Illumination ❖Illumination Principles Light can be described as waves with three properties: ➢Wavelength or color, measured in nm (nanometers) ➢Intensity ➢Polarization. SICK IVP, “Machine Vision Introduction,” 2006. 19

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2. Basic elements of machine vision system ❑ 2.2. Illumination ❖Illumination Principles ➢ The spectral response of a sensor is the sensitivity curve for different wavelengths. Spectral response of a gray scale CCD sensor. Maximum sensitivity is for green (500 nm). SICK IVP, “Machine Vision Introduction,” 2006. 20

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2. Basic elements of machine vision system ❑ 2.2. Illumination ❖Illumination Principles ➢ The optical axis is a thought line through the center of the lens, i.e. the direction the camera is looking. SICK IVP, “Machine Vision Introduction,” 2006. 21

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