Handbook of Image Processing and Computer Vision : Volume 3: From Pattern to Object / by Arcangelo Distante, Cosimo Distante.

Format:

Book

Author/Creator:

Distante, Arcangelo, author.

Distante, Cosimo, author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Optical data processing.

Machine learning.

Data structures (Computer science).

Image Processing and Computer Vision.

Machine Learning.

Data Structures.

Local Subjects:

Image Processing and Computer Vision.

Machine Learning.

Data Structures.

Physical Description:

1 online resource (XXIII, 676 pages) : 271 illustrations, 185 illustrations in color

Edition:

First edition 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

Across three volumes, the Handbook of Image Processing and Computer Vision 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. Volume 3 (From Pattern to Object) examines object recognition, neural networks, motion analysis, and 3D reconstruction of a scene. 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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-030-42378-0

9783030423780

Access Restriction:

Restricted for use by site license.