Computer Vision Methods for Fast Image Classification and Retrieval (Studies in Computational Intelligence, 821) - Hardcover

Scherer, Rafał

Hardcover

ISBN 10: 3030121941 ISBN 13: 9783030121945

Publisher: Springer, 2019

Synopsis

The book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as ‘hand-crafted features.’ It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images.

Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book’s main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions.

About this title

From the Back Cover

The book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as ‘hand-crafted features.’ It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images.

 

Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book’s main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions.

Edition details

• Publisher: Springer
• Publication date: 2019
• Language: English
• ISBN 10: 3030121941
• ISBN 13: 9783030121945
• Binding: Hardcover
• Edition number: 1
• Number of pages: 146