
Image Processing and Machine Learning, Volume 2
Advanced Topics in Image Analysis and Machine Learning
- 224 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Image Processing and Machine Learning, Volume 2
Advanced Topics in Image Analysis and Machine Learning
About this book
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.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Preface Volume II
- 1 Morphological Operations
- 2 Color Images
- 3 Geometric Operations in Images
- 4 Comparison and Recognition of Images
- 5 Mean-Shift Algorithm for Segmentation
- 6 Singular Value Decomposition in Image Processing
- Index