Image Processing and Machine Learning, Volume 1: Foundations of Image Processing

by Erik Cuevas, Alma Nayeli Rodríguez

Overview

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 first installment explores the fundamental concepts and techniques in image processing, starting with pixel operations and their properties and exploring spatial filtering, edge detection, image segmentation, corner detection, and geometric transformations. It provides a solid foundation for readers interested in understanding the core principles and practical applications of image processing, establishing the essential groundwork necessary for further explorations covered in Volume 2.

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

Product Details

ISBN-13:	9781032234588
Publisher:	CRC Press
Publication date:	02/16/2024
Pages:	224
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Erik Cuevas, Alma Nayeli Rodríguez

Table of Contents

Preface Volume 1. 1. Pixel Operations. 2. Spatial Filtering. 3. Edge Detection. 4. Segmentation and Processing of Binary Images. 5. Corner Detection. 6. Line Detection. Index.