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Image processing and machine learning [2 Vols.]

By: Cuevas, Erik.
Contributor(s): Rodríguez, Alma Nayeli.
Publisher: Boca Raton CRC Press 2024Description: Various pagings.ISBN: 9781032234588, 9781032660325.Subject(s): Image processing | Machine learningDDC classification: 006.6 | C894i
Contents:
v.1. Foundations of image processing, pg. xiii, 209p., 9781032234588: A186670; v.2.Advanced topics in image analysis and machine learning, pg. xiv, 223p., 9781032660325: A186671
Summary: Vol.1. 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. Vol.2. 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.
List(s) this item appears in: New arrival December 09 to 15, 2024
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Item type Current location Collection Call number Vol info Status Date due Barcode Item holds
Books Books PK Kelkar Library, IIT Kanpur
On Display 006.6 C894i v.1 (Browse shelf) v.1 Foundations of image processing Available A186670
Books Books PK Kelkar Library, IIT Kanpur
On Display 006.6 C894i v.2 (Browse shelf) v.2. Advanced topics in image analysis and machine learning Available A186671
Total holds: 0
Browsing PK Kelkar Library, IIT Kanpur Shelves , Collection code: On Display Close shelf browser
006.6 C894i v.1 Image processing and machine learning [2 Vols.] 006.6 C894i v.2 Image processing and machine learning [2 Vols.] 006.6 Z61t 3D computer vision 338 Op7 Optimization in industry

v.1. Foundations of image processing, pg. xiii, 209p., 9781032234588: A186670; v.2.Advanced topics in image analysis and machine learning, pg. xiv, 223p., 9781032660325: A186671

Vol.1. 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.

Vol.2. 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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