Handbook of Image Processing and Computer Vision

 
 
Springer (Verlag)
  • erscheint ca. am 23. August 2020
 
  • Buch
  • |
  • Hardcover
  • |
  • XLII, 1618 Seiten
978-3-030-38147-9 (ISBN)
 

This three-volume handbook presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously.

Topics and features: describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy; covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal; discusses the information recorded in a digital image, and the image processing algorithms that can improve the visual qualities of the image; reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration; presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest; examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration; provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networks.

This all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT/software and electronics industries involved in machine vision, imaging, and artificial intelligence.

1st ed. 2020
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • Fadenheftung
  • |
  • Gewebe-Einband
  • 541 farbige Abbildungen, 291 s/w Abbildungen
  • |
  • Bibliography; 541 Illustrations, color; 291 Illustrations, black and white
  • Höhe: 23.5 cm
  • |
  • Breite: 15.5 cm
  • |
  • Dicke: 0 mm
978-3-030-38147-9 (9783030381479)
10.1007/978-3-030-38148-6
weitere Ausgaben werden ermittelt

Dr. Cosimo Distante is a Research Scientist in Computer Vision and Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR).

Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. His research interests are in the fields of Computer Vision, Pattern Recognition, Machine Learning, and Neural Computation.

Volume 1: From Energy to Image

Image Formation Process

Radiometric Model

Color

Optical System

Digitization and Image Display

Properties of the Digital Image

Data Organization

Representation and Description of Forms

Image Enhancement Techniques

Volume 2: From Image to Pattern

Local Operations: Edging

Fundamental Linear Transforms

Geometric Transformations

Reconstruction of the Degraded Image: Restoration

Image Segmentation

Detectors and Descriptors of Interest Points

Volume 3: From Pattern to Objects

Object Recognition

RBF, SOM, Hopfield and Deep Neural Networks

Texture Analysis

Paradigms for 3D Vision

Shape from Shading

Motion Analysis

Camera Calibration and 3D Reconstruction

This three-volume handbook presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously.

Topics and features:

- Describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy
- Covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal
- Discusses the information recorded in a digital image, and the image processing algorithms that can improve the visual qualities of the image
- Reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration
- Presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest
- Examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration
- Provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networks

This all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT/software and electronics industries involved in machine vision, imaging, and artificial intelligence.

Dr. Cosimo Distante is a Research Scientist in Computer Vision and Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR). Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. His research interests are in the fields of Computer Vision, Pattern Recognition, Machine Learning, and Neural Computation.
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