Image Processing and Machine Learning, Volume 2 (Hardcover)

Erik Cuevas

ISBN 10: 1032660325 / ISBN 13: 9781032660325

Published by Taylor & Francis Ltd, London, 2024

About this Item

Hardcover. Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches.Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1.Written with instructors and students of image processing in mind, this books intuitive organization also contains appeal for app developers and engineers. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032660325

Bibliographic Details

Title: Image Processing and Machine Learning, ...

Publisher: Taylor & Francis Ltd, London

Publication Date: 2024

Binding: Hardcover

Condition: new

About this title

Synopsis:

Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches.

Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1.

Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers.

About the Author:

Erik Cuevas, Alma Nayeli Rodríguez