04982nam 22007695 450 991025545340332120200703154556.0981-10-6759-710.1007/978-981-10-6759-4(CKB)4100000001795005(DE-He213)978-981-10-6759-4(MiAaPQ)EBC5224841(PPN)223954209(EXLCZ)99410000000179500520180116d2017 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierContent-Based Image Retrieval[electronic resource] Ideas, Influences, and Current Trends /by Vipin Tyagi1st ed. 2017.Singapore :Springer Singapore :Imprint: Springer,2017.1 online resource (XXXIV, 378 p. 134 illus., 73 illus. in color.) 981-10-6758-9 Includes bibliographical references and index.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.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.Optical data processingData structures (Computer science)Pattern recognitionSignal processingImage processingSpeech processing systemsComputer science—MathematicsComputer mathematicsApplied mathematicsEngineering mathematicsImage Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Data Structures and Information Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/I15009Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XSignal, Image and Speech Processinghttps://scigraph.springernature.com/ontologies/product-market-codes/T24051Mathematical Applications in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/M13110Mathematical and Computational Engineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/T11006Optical data processing.Data structures (Computer science).Pattern recognition.Signal processing.Image processing.Speech processing systems.Computer science—Mathematics.Computer mathematics.Applied mathematics.Engineering mathematics.Image Processing and Computer Vision.Data Structures and Information Theory.Pattern Recognition.Signal, Image and Speech Processing.Mathematical Applications in Computer Science.Mathematical and Computational Engineering.006.6006.37Tyagi Vipinauthttp://id.loc.gov/vocabulary/relators/aut1062610BOOK9910255453403321Content-Based Image Retrieval2526888UNINA