Image Processing using Pulse-Coupled Neural Networks :
General Material Designation
[Book]
Other Title Information
Applications in Python
First Statement of Responsibility
by Thomas Lindblad, Jason M. Kinser.
EDITION STATEMENT
Edition Statement
3rd ed. 2013
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Berlin, Heidelberg
Name of Publisher, Distributor, etc.
Springer Berlin Heidelberg : Imprint : Springer
Date of Publication, Distribution, etc.
2013
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 ressource en ligne (XXIV, 238 p.) : 142 illustrations, 9 illustrations in color
SERIES
Series Title
Biological and Medical Physics, Biomedical Engineering
CONTENTS NOTE
Text of Note
Biological Models --; Programming in Python --; NumPy, SciPy and Python Image Library --; The PCNN and ICM --; Image Analysis --; Feedback and Isolation --; Recognition and Classification --; Texture Recognition --; Color and Multiple Channels --; Image Signatures --; Logic.
SUMMARY OR ABSTRACT
Text of Note
Image processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.