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Computer Vision Methods for Fast Image Classification and Retrieval: Studies in Computational Intelligence, cartea 821

Autor Rafał Scherer
en Limba Engleză Paperback – 28 oct 2020
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.
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Specificații

ISBN-13: 9783030121976
ISBN-10: 3030121976
Pagini: 137
Ilustrații: IX, 137 p. 85 illus., 55 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.22 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Preface.- Chapter 1. Introduction.- Chapter 2. Feature Detection.- Chapter 3. Image Indexing Techniques.- Chapter 4. Novel Methods for Image Description.- Chapter 5. Image Retrieval and Classification in Relational Databases etc.

Textul de pe ultima copertă

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.

Caracteristici

Highlights new research and techniques Presents methods for accelerating image retrieval and classi?cation in large datasets Includes selected methods that are designed to work directly in relational database management systems