04368nam 22007215 450 991025545340332120251113210250.0981-10-6759-710.1007/978-981-10-6759-4(CKB)4100000001795005(DE-He213)978-981-10-6759-4(MiAaPQ)EBC5224841(PPN)223954209(EXLCZ)99410000000179500520180116d2017 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierContent-Based Image Retrieval Ideas, Influences, and Current Trends /by Vipin Tyagi1st ed. 2017.Singapore :Springer Nature 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.Computer visionData structures (Computer science)Information theoryPattern recognition systemsSignal processingComputer scienceMathematicsEngineering mathematicsEngineeringData processingComputer VisionData Structures and Information TheoryAutomated Pattern RecognitionSignal, Speech and Image ProcessingMathematical Applications in Computer ScienceMathematical and Computational Engineering ApplicationsComputer vision.Data structures (Computer science)Information theory.Pattern recognition systems.Signal processing.Computer scienceMathematics.Engineering mathematics.EngineeringData 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.006.6006.37Tyagi Vipinauthttp://id.loc.gov/vocabulary/relators/aut1062610BOOK9910255453403321Content-Based Image Retrieval2526888UNINA