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Image Processing Using Pulse-Coupled Neural Networks

By: Lindblad, T [author.].
Contributor(s): Kinser, J.M [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.Edition: Second, Revised Edition.Description: XI, 164 p. 139 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540282938.Subject(s): Engineering | Biophysics | Biological physics | Optics | Optoelectronics | Plasmons (Physics) | Statistics | Materials -- Surfaces | Thin films | Engineering | Signal, Image and Speech Processing | Surfaces and Interfaces, Thin Films | Optics, Optoelectronics, Plasmonics and Optical Devices | Biophysics and Biological Physics | Statistical Theory and Methods | Engineering, generalDDC classification: 621.382 Online resources: Click here to access online
Contents:
and Theory -- Theory of Digital Simulation -- Automated Image Object Recognition -- Image Fusion -- Image Texture Processing -- Image Signatures -- Miscellaneous Applications -- Hardware Implementations.
In: Springer eBooksSummary: This is the first book to explain and demonstrate the tremendous ability of Pulse-Coupled Neural Networks (PCNNs) when applied to the field of image processing. PCNNs and their derivatives are biologically inspired models that are powerful tools for extracting texture, segments, and edges from images. As these attributes form the foundations of most image processing tasks, the use of PCNNs facilitates traditional tasks such as recognition, foveation, and image fusion. PCNN technology has also paved the way for new image processing techniques such as object isolation, spiral image fusion, image signatures, and content-based image searches. This volume contains examples of several image processing applications, as well as a review of hardware implementations.
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E books E books PK Kelkar Library, IIT Kanpur
Available EBK7598
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and Theory -- Theory of Digital Simulation -- Automated Image Object Recognition -- Image Fusion -- Image Texture Processing -- Image Signatures -- Miscellaneous Applications -- Hardware Implementations.

This is the first book to explain and demonstrate the tremendous ability of Pulse-Coupled Neural Networks (PCNNs) when applied to the field of image processing. PCNNs and their derivatives are biologically inspired models that are powerful tools for extracting texture, segments, and edges from images. As these attributes form the foundations of most image processing tasks, the use of PCNNs facilitates traditional tasks such as recognition, foveation, and image fusion. PCNN technology has also paved the way for new image processing techniques such as object isolation, spiral image fusion, image signatures, and content-based image searches. This volume contains examples of several image processing applications, as well as a review of hardware implementations.

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