Inspection of any production process can be tedious and repetitive and humans make mistakes. This book shows how even natural products with a high degree of variation can be subjected to the untiring and less error-prone inspection of a machine. Gives practical advice on the implementation of systems for the inspection of a wide variety of naturally occurring materials from stones to live animals.
Machine vision technology has revolutionised the process of automated inspection in manufacturing. The specialist techniques required for inspection of natural products, such as food, leather, textiles and stone is still a challenging area of research. Topological variations make image processing algorithm development, system integration and mechanical handling issues much more complex. The practical issues of making machine vision systems operate robustly in often hostile environments together with the latest technological advancements are reviewed in this volume. Features:
- Case studies based on real-world problems to demonstrate the practical application of machine vision systems.
- In-depth deillegalscription of system components including image processing, illumination, real-time hardware, mechanical handling, sensing and on-line testing.
- Systems-level integration of constituent technologies for bespoke applications across a variety of industries.
- A diverse range of example applications that a system may be required to handle from live fish to ceramic tiles.
Machine Vision for the Inspection of Natural Products will be a valuable resource for researchers developing innovative machine vision systems in collaboration with food technology, textile and agriculture sectors. It will also appeal to practising engineers and managers in industries where the application of machine vision can enhance product safety and process efficiency.
|This book will sell because it enables manufacturers of products involving natural materials to do so more reliably, safely and efficiently while relieving humans of the tedious and repetitive tasks previously associated with the inspection of less regular or well ordered products.
List of Contributors 1. Like Two Peas in a PodB.G. Batchelor Editorial Introduction 1.1 Advantages of Being Able to See1.2 Machine Vision 1.2.1 Model for Machine Vision Systems1.2.2 Applications Classified by Task1.2.3 Other Applications of Machine Vision 1.2.4 Machine Vision Is Not Natural 1.3 Product Variability 1.3.1 Linear Dimensions 1.3.2 Shape1.3.3 Why Physical Tolerances Matter 1.3.4 Flexible and Articulated Objects1.3.5 Soft and Semi-fluid Objects 1.3.6 Colour Variations1.3.7 Transient Phenomena1.3.8 Very Complex Objects1.3.9 Uncooperative Objects1.3.10 Texture 1.4 Systems Issues 1.5 References 2. Basic Machine Vision TechniquesB.G. Batchelor and P.F. Whelan Editorial Introduction 2.1 Representation of Images 2.2 Elementary Image Processing Functions2.2.1 Monadic Point-by-point Operators 2.2.2 Dyadic Point-by-point Operators 2.2.3 Local Operators2.2.4 Linear Local Operators 2.2.5 Non-linear Local Operators2.2.6 N-tuple Operators2.2.7 Edge Effects 2.2.8 Intensity Histogram [hpi, hgi, he, hgc} 2.3 Binary Images2.3.1 Measurements on Binary Images 2.3.2 Shape Deillegalscriptors 2.4 Binary Mathematical Morphology 2.4.1 Opening and Closing Operations 2.4.2 Structuring Element Decomposition 2.5 Grey-scale Morphology2.6 Global Image Transforms2.6.1 Hough Transform2.6.2 Two-dimensional Discrete Fourier Transform2.7 Texture Analysis2.7.1 Statistical Approaches2.7.2 Co-occurrence Matrix Approach2.7.3 Structural Approaches2.7.4 Morphological Texture Analysis2.8 Implementation Considerations2.8.1 Morphological System Implementation 2.9 Commercial Devices2.9.1 Plug-in Boards: Frame-grabbers 2.9.2 Plug-in Boards: Dedicated Function 2.9.3 Self-contained Systems 2.9.4 Turn-key Systems2.9.5 Software 2.10 Further Remarks 2.11References 3. Intelligent Image ProcessingB.G. Batchelor Editorial Introduction 3.1 Why We Need Intelligence 3.2 Pattern Recognition 3.2.1 Similarity and Distance 3.2.2 Compactness Hypothesis 3.2.3 Pattern Recognition Models3.3 Rule-based Systems3.3.1 How Rules are Used3.3.2 Combining Rules and Image Processing3.4 Colour Recognition 3.4.1 RGB Representation3.4.2 Pattern Recognition3.4.3 Programmable Colour Filter3.4.4 Colour Triangle 3.5 Methods and Applications3.5.1 Human Artifacts 3.5.2 Plants3.5.3 Semi-processed Natural Products 3.5.4 Food Products 3.6 Concluding Remarks 3.7 References 4. Using Natural Phenomena to Aid Food Produce InspectionG. LongEditorial Introduction 4.1 Introduction 4.2 Techniques to Exploit Natural Phenomena 4.3 Potato Sizing and Inspection 4.4 Stone Detection in Soft Fruit Using Auto-fluorescence 4.5 Brazil Nut Inspection4.6 Intact Egg Inspection4.7 Wafer Sizing4.8 Enrobed Chocolates4.9 Conclusion4.10 References 5. Colour Sorting in the Food IndustryS.C. Bee and M.J. Honeywood Editorial Introduction 5.1 Introduction 5.2 The Optical Sorting Machine 5.2.1 The Feed System5.2.2 The Optical System 5.2.3 The Ejection System 5.2.4 The Image Processing Algorithms 5.3 Assessment of Objects for Colour Sorting 5.3.1 Spectrophotometry 5.3.2 Monochromatic Sorting 5.3.3 Bichromatic Sorting 5.3.4 Dual Monochromatic Sorting5.3.5 Trichromatic Sorting 5.3.6 Fluorescence Techniques 5.3.7 Infrared Techniques 5.3.8 Optical Sorting with Lasers5.4 The Optical Inspection System5.4.1 Illumination 5.4.2 Background and Aperture 5.4.3 Optical Filters5.4.4 Detectors 5.5 The Sorting System 5.5.1 Feed5.5.2 Ejection 5.5.3 Cleaning and Dust Extraction 5.5.4 The Electronic Processing System 5.6 The Lim
Like Two Peas in a Pod.- Basic Machine Vision Techniques.- Intelligent Image Processing.- Using Natural Phenomena to Aid Food Produce Inspection.- Colour Sorting in the Food Industry.- Surface Defect Detection on Ceramics.- On-line Automated Visual Grading of Fruit: Practical Challenges.- Vision-based Quality Control in Poultry Processing.- Quality Classification of Wooden Surfaces Using Gabor Filters and Genetic Feature Optimisation.- An Intelligent Approach to Fabric Defect Detection in Textile Processes.- Automated Cutting of Natural Products: A Practical Packing Strategy.- Model-based Stereo Imaging for Estimating the Biomass of Live Fish.- A System for Estimating the Size and Shape of Live Pigs.- Sheep Pelt Inspection.- Design of Object Location Algorithms and Their Use for Food and Cereals Inspection.- X-ray Bone Detection in Further Processed Poultry Production.- Final Remarks.
Inhaltsverzeichnis
Like Two Peas in a Pod.- Basic Machine Vision Techniques.- Intelligent Image Processing.- Using Natural Phenomena to Aid Food Produce Inspection.- Colour Sorting in the Food Industry.- Surface Defect Detection on Ceramics.- On-line Automated Visual Grading of Fruit: Practical Challenges.- Vision-based Quality Control in Poultry Processing.- Quality Classification of Wooden Surfaces Using Gabor Filters and Genetic Feature Optimisation.- An Intelligent Approach to Fabric Defect Detection in Textile Processes.- Automated Cutting of Natural Products: A Practical Packing Strategy.- Model-based Stereo Imaging for Estimating the Biomass of Live Fish.- A System for Estimating the Size and Shape of Live Pigs.- Sheep Pelt Inspection.- Design of Object Location Algorithms and Their Use for Food and Cereals Inspection.- X-ray Bone Detection in Further Processed Poultry Production.- Final Remarks.
Klappentext
Machine vision technology has revolutionised the process of automated inspection in manufacturing. The specialist techniques required for inspection of natural products, such as food, leather, textiles and stone is still a challenging area of research. Topological variations make image processing algorithm development, system integration and mechanical handling issues much more complex. The practical issues of making machine vision systems operate robustly in often hostile environments together with the latest technological advancements are reviewed in this volume. Features:
- Case studies based on real-world problems to demonstrate the practical application of machine vision systems.
- In-depth deillegalscription of system components including image processing, illumination, real-time hardware, mechanical handling, sensing and on-line testing.
- Systems-level integration of constituent technologies for bespoke applications across a variety of industries.
- A diverse range of example applications that a system may be required to handle from live fish to ceramic tiles.
Machine Vision for the Inspection of Natural Products will be a valuable resource for researchers developing innovative machine vision systems in collaboration with food technology, textile and agriculture sectors. It will also appeal to practising engineers and managers in industries where the application of machine vision can enhance product safety and process efficiency.
This book will sell because it enables manufacturers of products involving natural materials to do so more reliably, safely and efficiently while relieving humans of the tedious and repetitive tasks previously associated with the inspection of less regular or well ordered products.
