Advances and Applications of Optimised Algorithms in Image Processing

ISBN-13: 9783319485492 / Angielski / Twarda / 2016 / 178 str.

Diego Oliva; Erik Cuevas

Opis

This book presents a study of the use of optimization algorithms in complex image processing problems. The problems selected explore areas ranging from the theory of image segmentation to the detection of complex objects in medical images. Furthermore, the concepts of machine learning and optimization are analyzed to provide an overview of the application of these tools in image processing. The material has been compiled from a teaching perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, and can be used for courses on Artificial Intelligence, Advanced Image Processing, Computational Intelligence, etc. Likewise, the material can be useful for research from the evolutionary computation, artificial intelligence and image processing communities.

Recenzje

"This book examines the application of optimization to common problems in image processing: segmentation, template matching, and shape detection. ... Readers interested in improving the accuracy or performance of image processing systems would do well to read this book." (Creed Jones, Computing Reviews, May, 2017)

Spis treści

An introduction to machine learning.-  Optimization.-  Electromagnetism – Like Optimization Algorithm: An Introduction.-  Digital image segmentation as an optimization problem.- Template matching using a physical inspired algorithm.-Detection of circular shapes in digital images.-  A medical application: Blood cell segmentation by circle detection.- An EMO Improvement: Opposition-Based Electromagnetism-Like for Global Optimization

Blurb

This book presents a study of the use of optimization algorithms in complex image processing problems. The problems selected explore areas ranging from the theory of image segmentation to the detection of complex objects in medical images. Furthermore, the concepts of machine learning and optimization are analyzed to provide an overview of the application of these tools in image processing.

 

The material has been compiled from a teaching perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, and can be used for courses on Artificial Intelligence, Advanced Image Processing, Computational Intelligence, etc. Likewise, the material can be useful for research from the evolutionary computation, artificial intelligence and image processing co