Издательство Springer, 2012, -2291 pp.The automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture – lenses, cameras, scanners and light sources – are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in inspecting and handling different types of object.Machine Vision for Industrial Applications. Inspecting Natural and Other Variable Objects. Human and Animal Vision. Colour Vision. Light and Optics. Telecentric, Fresnel and Micro Lenses. Illumination Sources. Lighting-Viewing Methods. Laser Scanners. Cameras. Selecting Cameras for Machine Vision. X-Ray Inspection. Illumination-Invariant Image Processing. Basic Machine Vision Techniques. Imaging and Range Image Processing. Colour Recognition. Algorithms, Approximations and Heuristics. Object Location Using the HOUGH Transform. Morphological Image Processing. Image Processing Using Finite-State Machines. QT – Prototyping Image Processing System. NeatVision: Development Environment for Machine Vision Engineers. Intelligent Image Processing Using Prolog. Pattern Recognition. Implementing Machine Vision Systems Using FPGAs. Very Low-Cost In-Process Gauging System. Automated Handling of Coils with Flying Leads. A Telecentric Vision System for Broach Verification. Challenges of Low Angle Metal Surface (Crosshead) Inspection. A Machine Vision System for Quality Grading of Painted Slates. Inspecting Glass Bottles and Jars. Stemware Inspection System. Restoration of Missing Boundary Segments in Shattered Glass. Determination of Geometric Stability of Glass Substrates. Glass Thickness Measurement Using Morphology. Inspecting Food Products. Automatic Produce Grading System. Analysing the Creasing Properties of Fabric. Environmental, Social and Ethical Issues. Lighting-Viewing Methods. QT Image Processing Functions. A: Glossary. B: MV Questionnaire. C: Proverbs. D: MV Knowledge Base. E: Robot Vision: Calibration. F: Object Location and Orientation. G: Image Catalogue. H: Connecting QT to External Devices. I: Information Sources.
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