Editors:
- Covers most of the nature-inspired optimization algorithms in a single resource
- Provides step-by-step algorithm coverage to facilitate implementation for budding researchers
- Addresses specific application areas, helping researchers choose a specific optimization area for their application
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 150)
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Table of contents (12 chapters)
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Front Matter
About this book
This book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially. These accuracy and complexity are a major area of concern when it comes to practical applications. However, these optimization techniques have not yet been fully explored in the context of imaging applications. By presenting interdisciplinary concepts, ranging from optimization to image processing, the book appeals to a broad readership, while also encouraging budding engineers to pursue and employ innovative nature-inspired techniques for image processing applications.
Editors and Affiliations
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Department of Electronics and Communication Engineering, Karunya University , Coimbatore, India
Jude Hemanth
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Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad , Arad, Romania
Valentina Emilia Balas
Bibliographic Information
Book Title: Nature Inspired Optimization Techniques for Image Processing Applications
Editors: Jude Hemanth, Valentina Emilia Balas
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-319-96002-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-319-96001-2Published: 28 September 2018
Softcover ISBN: 978-3-030-07126-4Published: 31 January 2019
eBook ISBN: 978-3-319-96002-9Published: 19 September 2018
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XIV, 297
Number of Illustrations: 130 b/w illustrations
Topics: Signal, Image and Speech Processing, Computer Imaging, Vision, Pattern Recognition and Graphics, Optimization