Industrial Image Processing: Visual Quality Control in Manufacturing

✍ Scribed by Christian Demant, Bernd Streicher-Abel, Carsten Garnica

• Publisher: Springer
• Year: 2013
• Tongue: English
• Leaves: 378
• Edition: 2nd revised ed. 2013
• Category: Library

✦ Synopsis

This practical introduction focuses on how to design integrated solutions for industrial vision tasks from individual algorithms. The book is now available in a revised second edition that takes into account the current technological developments, including camera technology and color imaging processing. It gives a hands-on guide for setting up automated visual inspection systems using real-world examples and the NeuroCheck® standard software that has proven industrial strength integrated in thousands of applications in real-world production lines. Based on many years of experience in industry, the authors explain all the essential details encountered in the creation of vision system installations. With example material and a demo version of the software found on "extras.springer.com" readers can work their way through the described inspection tasks and carry out their own experiments.

✦ Table of Contents

Foreword
Preface
Contents
1 Introduction
1.1…Why Write Another Book About Image Processing?
1.2…Possibilities and Limitations
1.3…Types of Inspection Tasks
1.4…Structure of Image Processing Systems
1.4.1 Hardware
1.4.2 Signal Flow in Process Environment
1.4.3 Signal Flow Within the Image Processing System
1.5…Process Model
1.6…Introductory Example
1.6.1 Optical Character Recognition
1.6.2 Thread Depth
1.6.3 Presence Verification
1.7…From Here
References
2 Overview: Image Preprocessing
2.1…Gray Scale Transformation
2.1.1 Look-Up Tables
2.1.2 Linear Gray Level Scaling
2.1.3 Contrast Enhancement
2.1.4 Histogram Equalization
2.1.5 Local Contrast Enhancement
2.2…Image Arithmetic
2.2.1 Image Addition and Averaging
2.2.2 Image Subtraction
2.2.3 Minimum and Maximum of Two Images
2.2.4 Shading Correction
2.3…Linear Filters
2.3.1 Local Operations and Neighborhoods
2.3.2 Principle of Linear Filters
2.3.3 Smoothing Filters
2.3.4 Edge Filters
2.4…Median Filter
2.5…Morphological Filters
2.6…Other Non-linear Filters
2.7…Coordinate Transformations
2.8…Integral Transformations
2.9…Summary
References
3 Positioning
3.1…Position of an Individual Object
3.1.1 Positioning Using the Entire Object
3.1.2 Positioning Using an Edge
3.2…Orientation of an Individual Object
3.2.1 Orientation Computation Using Principal Axis
3.2.2 Distance-Versus-Angle Signature
3.3…Robot Positioning
3.3.1 Application
3.3.2 Image Processing Components
3.3.3 Position Determination on One Object
3.3.4 Orientation of an Object Group
3.3.5 Comments Concerning Position Adjustment
3.4…Summary
References
4 Overview: Segmentation
4.1…Regions of Interest (ROIs)
4.2…Binary Segmentation
4.2.1 Thresholds
4.2.2 Threshold Determination from Histogram Analyses
4.2.3 Gray Level Histograms
4.2.4 Generalizations of Thresholding
4.3…Contour Tracing
4.3.1 Connectedness
4.3.2 Generating Object Contours
4.3.3 Contour Representation
4.4…Template Matching
4.4.1 Basic Operation
4.4.2 Optimizing Template Matching
4.4.3 Comments on Template Matching
4.4.4 Edge-Based Object Search
4.5…Edge Detection
4.5.1 Edge Probing in Industrial Image Scenes
4.5.2 Edge Search with Subpixel Accuracy
4.6…Summary
References
5 Mark Identification
5.1…Bar Code Identification
5.1.1 Principle of Gray-Level-Based Bar Code Identification
5.1.2 Types of Bar Codes
5.1.3 Examples for Industrial Bar Code Identification
5.1.4 Two-Dimensional Codes
5.2…Character Recognition
5.2.1 Laser-Etched Characters on an IC
5.2.2 Basic Configuration of Character Recognition
5.2.3 Fundamental Structure of a Classifier Application
5.2.4 Position Adjustment on the IC
5.2.5 Improving Character Quality
5.2.6 Optimization in Operation
5.3…Recognition of Pin-Marked Digits on Metal
5.3.1 Illumination
5.3.2 Preprocessing
5.3.3 Segmentation and Classification
5.4…Block Codes on Rolls of Film
5.5…Print Quality Inspection
5.5.1 Methods
5.5.2 Print Quality Inspection in Individual Regions
5.5.3 Print Quality Inspection with Automatic Subdivision
5.6…Summary
References
6 Overview: Classification
6.1…What is Classification?
6.2…Classification as Function Approximation
6.2.1 Basic Terms
6.2.2 Statistical Foundations
6.2.3 Defining Classifiers
6.3…Instance-Based Classifiers
6.3.1 Nearest Neighbor Classifier
6.3.2 RCE Networks
6.3.3 Vector Quantization
6.3.4 Template Matching
6.3.5 Comments on Instance-Based Classifiers
6.4…Function-Based Classifiers
6.4.1 Polynomial Classifier
6.4.2 Multilayer Perceptron-Type Neural Networks
6.5…Comments on the Application of Neural Networks
6.5.1 Composition of the Training Set
6.5.2 Feature Scaling
6.5.3 Rejection
6.5.4 Differentiation from Other Classifiers
6.6…Summary
References
7 Gauging
7.1…Gauging Tasks
7.2…Simple Gauging
7.2.1 Centroid Distances
7.2.2 Contour Distances
7.2.3 Angle Measurements
7.3…Shape Checking on a Punched Part
7.3.1 Inspection Task
7.3.2 Modeling Contours by Lines
7.3.3 Measuring the Contour Angle
7.4…Angle Gauging on Toothed Belt
7.4.1 Illumination Setup
7.4.2 Edge Creation
7.5…Shape Checking on Injection-Molded Part
7.5.1 Computing Radii
7.5.2 Comments on Model Circle Computation
7.6…High Accuracy Gauging on Thread Flange
7.6.1 Illumination and Image Capture
7.6.2 Subpixel-Accurate Gauging of the Thread Depth
7.7…Calibration
7.7.1 Calibration Mode
7.7.2 Inspection-Related Calibration
7.8…Summary
Reference
8 Overview: Image Acquisition and Illumination
8.1…Solid-State Sensors
8.1.1 Introduction
8.1.2 CCD Sensors
8.1.3 CMOS Sensors
8.1.4 Special Types
8.1.5 Color Sensors
8.1.6 Properties of Sensors
8.2…Digital Cameras
8.2.1 Control of Image Capture
8.2.2 Capturing Color Images
8.2.3 Characteristic Values of Digital Cameras
8.2.4 Operating Conditions in Industrial Environments
8.3…Image Data Transfer
8.3.1 CameraLinkreg
8.3.2 FireWirereg
8.3.3 USB
8.3.4 Gigabit Ethernet
8.4…Line-Scan Cameras
8.4.1 Types of Line-Scan Camera Applications
8.4.2 Spatial Resolution of Line-Scan Cameras
8.4.3 Illumination for Line-Scan Cameras
8.4.4 Control of Line-Scan Cameras
8.5…Optical Foundations
8.5.1 f-number
8.5.2 Laws of Imaging
8.5.3 Depth of Field
8.5.4 Typical Capturing Situations
8.5.5 Aberrations
8.5.6 Lens Determination
8.5.7 Special Lens Types
8.6…Illumination Technology
8.6.1 Light Sources
8.6.2 Front Lighting
8.6.3 Back Lighting
8.7…Summary
References
9 Presence Verification
9.1…Presence Verification Using PTZ Cameras
9.1.1 Inspection Part Geometry
9.1.2 Illumination
9.1.3 Positioning
9.1.4 Object Detection
9.1.5 Verification of Results
9.2…Simple Gauging for Assembly Verification
9.2.1 Illumination
9.2.2 Inspection Criteria
9.2.3 Object Creation and Measurement Computation
9.2.4 Position Adjustment
9.3…Presence Verification Using Classifiers
9.3.1 Illumination
9.3.2 Check of Crimping
9.3.3 Type Verification of the Flange
9.4…Contrast-Free Presence Verification
9.5…Presence Verification Using Line-Scan Cameras
9.5.1 Inspection of Cylindrical Parts with Area-Scan Cameras
9.5.2 Inspection of a Valve Body
9.5.3 Notes
9.6…Summary
10 Overview: Object Features
10.1…Basic Geometric Features
10.1.1 Enclosing Rectangle
10.1.2 Area and Perimeter
10.1.3 Centroid Coordinates
10.1.4 Axes and Radii
10.2…Shape Descriptors
10.2.1 Contour Curvature
10.2.2 Fiber Features
10.2.3 Euler Number
10.2.4 Moments and Fourier Descriptors
10.3…Gray Level Features
10.3.1 First-Order Statistics
10.3.2 Textural Features
10.4…Summary
References
11 Color Image Processing
11.1…Color Identification
11.1.1 Evaluation Strategy
11.1.2 Illumination and Image Capture
11.1.3 Color Classification
11.1.4 Selecting a Camera Image for Character Recognition
11.1.5 Recognition of Writing
11.2…Color Segmentation
11.2.1 Illumination
11.2.2 Color Classification
11.2.3 Segmentation
11.2.4 Presence Verification
11.3…Summary
References
12 Implementation of Industrial Image Processing Applications
12.1…Image Processing Projects
12.2…Process Integration
12.3…Outlook
Reference
Appendix AMathematical Notes
Appendix BSoftware Download
Appendix CWeblinks to Industrial Image Processing
Index