Nature Inspired Optimization for Image Processing

1st Edition

Vasuki A

Chapman and Hall/CRC
June 24, 2020 Forthcoming
Reference - 280 Pages - 125 B/W Illustrations
ISBN 9780367255985 - CAT# K424353

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Nature Inspired Optimization Algorithms is a comprehensive book on the most popular optimization algorithms that are based on nature. It starts with an overview of optimization and goes from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of nature inspired optimization techniques. The study of the intelligent survival strategies of animals, birds and insects in a hostile and ever-changing environment has led to the development of techniques emulating their behaviour. Nature provides us with simple solutions to complex problems in an effective and adaptive manner.

This book is a valuable resource for engineers, researchers, faculty and students who are devising optimum solutions to any type of problem. The problems range from computer science to economics covering diverse areas that require maximizing output and minimizing resources and this is the crux of all optimization algorithms. The book is a lucid description of fifteen of the existing important optimization algorithms that are based on swarm intelligence and superior in performance.


  • Detailed description of the algorithms along with pseudocode and flowchart
  • Easily translatable to program code that is also readily available in Mathworks website for some of the algorithms
  • Simple examples to demonstrate the optimization strategies have been given wherever possible that makes understanding easier
  • Standard applications and benchmark datasets for testing and validating the algorithms have been enumerated

This book is a reference for under-graduate and post-graduate students. It will be useful to faculty members teaching the subject on optimization. It also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature inspired optimization algorithms are unconventional and this makes them more efficient than their traditional counterparts.


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