Biological and Medical Physics, Biomedical Engineering

Image Processing using Pulse-Coupled Neural Networks

Applications in Python

Authors: Lindblad, Thomas, Kinser, Jason

  • Explains how to learn from nature image recognition
  • Applies pulse-coupled neural networks to image processing
  • Displays many applications accompanied by Python scripts
  • Considers a wide variety of image processing applications
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  • ISBN 978-3-642-36877-6
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  • ISBN 978-3-642-36876-9
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Softcover $149.00
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  • ISBN 978-3-642-44033-5
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About this book

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.

About the authors

Thomas Lindblad got his Ph.D. at the University of Stockholm in 1974, became associate professor two years later. Dr. Lindblad started his research career in nuclear structure and particle physics with a special interest in detector systems. He soon became the head of the section for Measuring Techniques and Information Processing at the Manne Siegbahn Institute of Physics. He was a frequent visitor to laboratories in Oak Ridge, Berkeley, Orsay, Grenoble and Darmstadt. Later professor Lindblad took a special interest in teaching, started Environmental Physics at the Royal Institute of Technology, Department of Physics, where he also was the director of undergraduate studies for several years. During this time his research interests focused on sensor techniques of different kinds and feature extraction of torrent data flows. A special interest was always the use of neural network hardware with applications to these fields and to diagnostics and environmental monitoring.


Jason Kinser received a D.Sc. in Optics and Electro-Optical Systems in 1994 and an M.S. in Physics in 1987. He joined Alabama A&M in 1994 as an associate research professor as a founding member of the Center for Applied Optical Sciences. He joined George Mason University in 1997 and is now an associate professor in the School of Physics and Computational Sciences at GMU. He has been a visiting scientist at the Royal Institute of Technology (Stockholm) and the Korean University (Seoul). He has also been a visiting scientist at Lawrence-Berkeley National Lab and an external examiner at the University of Mauritius. His research interests started with optical and image information processing including pulse image processing and now extends into processing of data existing in multiple domains.

Table of contents (11 chapters)

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-642-36877-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $149.00
price for USA
  • ISBN 978-3-642-36876-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $149.00
price for USA
  • ISBN 978-3-642-44033-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Image Processing using Pulse-Coupled Neural Networks
Book Subtitle
Applications in Python
Authors
Series Title
Biological and Medical Physics, Biomedical Engineering
Copyright
2013
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-36877-6
DOI
10.1007/978-3-642-36877-6
Hardcover ISBN
978-3-642-36876-9
Softcover ISBN
978-3-642-44033-5
Series ISSN
1618-7210
Edition Number
3
Number of Pages
XXIV, 238
Additional Information
3rd ed.
Topics