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Optoelectronics in machine vision-based theories and applications / Moises Rivas-Lopez, Oleg Sergiyenko, Wendy Flores-Fuentes, and Julio Cesar Rodriguez-Quinonez, editors. — 1 online resource (26 PDFs (xxv, 433 pages)) — <URL:http://elib.fa.ru/ebsco/1856898.pdf>.

Record create date: 7/25/2018

Subject: Computer vision — Industrial applications.; Optoelectronic devices.; Industrial electronics.; TECHNOLOGY & ENGINEERING / Mechanical; Computer vision — Industrial applications.; Industrial electronics.; Optoelectronic devices.

Collections: EBSCO

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"This book focuses on optoelectronic sensors, 3D & 2D machine vision technologies, robot navigation, control schemes, motion controllers, intelligent algorithms, agriculture applications and other vision systems. It covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring"--.

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Table of Contents

  • Title Page
  • Copyright Page
  • Book Series
  • Editorial Advisory Board
  • Table of Contents
  • Detailed Table of Contents
  • Preface
  • Acknowledgment
  • Section 1: Optical Detectors for Selected Applications
    • Chapter 1: Zeolite-Based Optical Detectors
    • Chapter 2: Analog Circuit of Light Detector for CMOS Image Sensor
    • Chapter 3: Optoelectronic Differential Cloudy Triangulation Method for Measuring Geometry of Hot Moving Objects
    • Chapter 4: Surface Measurement Techniques in Machine Vision
  • Section 2: Machine Vision for Modeling the Human Approach
    • Chapter 5: Leveraging Models of Human Reasoning to Identify EEG Electrodes in Images With Neural Networks
    • Chapter 6: Object-Oriented Logic Programming of Intelligent Visual Surveillance for Human Anomalous Behavior Detection
    • Chapter 7: Moving Object Classification Under Illumination Changes Using Binary Descriptors
    • Chapter 8: Machine Vision Application on Science and Industry
  • Section 3: Machine Vision for Structural Health Monitoring
    • Chapter 9: Application of Computer Vision Technology to Structural Health Monitoring of Engineering Structures
    • Chapter 10: Machine Vision-Based Application to Structural Analysis in Seismic Testing by Shaking Table
    • Chapter 11: Methods to Reduce the Optical Noise in a Real-World Environment of an Optical Scanning System for Structural Health Monitoring
  • Section 4: Technical Vision for Avoiding Obstacles and Autonomous Navigation
    • Chapter 12: Mobile Robot Path Planning Using Continuous Laser Scanning
    • Chapter 13: Methods and Algorithms for Technical Vision in Radar Introscopy
  • Compilation of References
  • About the Contributors
  • Index

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