Computer Vision Methods for Fast Image Classifcation and Retrieval: 821 - Rilegato

Scherer, Rafal

Rilegato

ISBN 10: 3030121941 ISBN 13: 9783030121945

Casa editrice: Springer-Nature New York Inc, 2019

Riassunto

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.

Su questo libro

Dalla quarta di copertina

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.

Dettagli dell?edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2019
• ISBN 10: 3030121941
• ISBN 13: 9783030121945
• Rilegatura: Copertina rigida
• Lingua: Inglese
• Numero edizione: 1
• Numero di pagine: 137
• Contatto del produttore: non disponibile