1.

Record Nr.

UNINA9910255453403321

Autore

Tyagi Vipin

Titolo

Content-Based Image Retrieval : Ideas, Influences, and Current Trends / / by Vipin Tyagi

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2017

ISBN

981-10-6759-7

Edizione

[1st ed. 2017.]

Descrizione fisica

1 online resource (XXXIV, 378 p. 134 illus., 73 illus. in color.)

Disciplina

006.6

006.37

Soggetti

Computer vision

Data structures (Computer science)

Information theory

Pattern recognition systems

Signal processing

Computer science - Mathematics

Engineering mathematics

Engineering - Data processing

Computer Vision

Data Structures and Information Theory

Automated Pattern Recognition

Signal, Speech and Image Processing

Mathematical Applications in Computer Science

Mathematical and Computational Engineering Applications

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Chapter 1. Introduction to Image Retrieval -- Chapter 2. Image Features -- Chapter 3. Content-based Multimedia Information Retrieval: State-of-the-art and Challenges -- Chapter 4. Images Matching through Region-based Similarity Technique -- Chapter 5. Visual Features In Image Retrieval Through CBIR -- Chapter 6. Content based Image Retrieval -- Chapter 7. Mathematical Tools for Image Retrieval -- Chapter 8. Text based Image Retrieval -- Chapter 9. Content based Image Retrieval of Texture Images -- Chapter 10.



Content based Image Retrieval of Natural Images -- Chapter 11. Color based Image Retrieval -- Chapter 12. Shape based Image Retrieval -- Chapter 13. Geographical image Based Retrieval -- Chapter 14. Query Processing Issues in Region-based Image Retrieval -- Chapter 15. Research Topics for Next Generation Content based Image Retrieval -- Bibliography -- Appendix A: Image Databases.

Sommario/riassunto

The book describes several techniques used to bridge the semantic gap and reflects on recent advancements in content-based image retrieval (CBIR). It presents insights into and the theoretical foundation of various essential concepts related to image searches, together with examples of natural and texture image types. The book discusses key challenges and research topics in the context of image retrieval, and provides descriptions of various image databases used in research studies. The area of image retrieval, and especially content-based image retrieval (CBIR), is a very exciting one, both for research and for commercial applications. The book explains the low-level features that can be extracted from an image (such as color, texture, shape) and several techniques used to successfully bridge the semantic gap in image retrieval, making it a valuable resource for students and researchers interested in the area of CBIR alike.