Image Processing and Machine Learning, Volume 2: Advanced Topics in Image Analysis and Machine Learning, 1st Edition eBook

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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.

This is a digital product.

Image Processing and Machine Learning, Volume 2: Advanced Topics in Image Analysis and Machine Learning 1st Edition is written by Erik Cuevas; Alma Nayeli Rodríguez and published by Chapman & Hall. The Digital and eTextbook ISBNs for Image Processing and Machine Learning, Volume 2 are 9781003829188, 100382918X and the print ISBNs are 9781032660325, 1032660325. Additional ISBNs for this eTextbook include 9781032662459, 9781032662466, 9781003829140.