In CBIR the most common feature used are shape, colors, texture etc. To improve the accuracy of retrieval, it must look on the far side the classical features. The features which could easily be extracted from data could be considered. One of such feature is directionality of the image texture. Directional information can be represented in a compact manner by using transform like wavelet, Gabor, Radon etc. In this book we address this problem of using directional information to increase accuracy of CBIR. Content-based image retrieval (CBIR), additionally called question by image content (QBIC) and content-based visual info retrieval (CBVIR) is that the application of laptop vision techniques to the image retrieval drawback, that is, the matter of checking out digital pictures in giant databases. In this book we have compared classical histogram method for image retrieval with retrieval using Gabor, Wavelet, Complex Wavelet, Radon transform and Ridgelet transform. Image retrieval performance is estimated by using Precession and Recall.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In CBIR the most common feature used are shape, colors, texture etc. To improve the accuracy of retrieval, it must look on the far side the classical features. The features which could easily be extracted from data could be considered. One of such feature is directionality of the image texture. Directional information can be represented in a compact manner by using transform like wavelet, Gabor, Radon etc. In this book we address this problem of using directional information to increase accuracy of CBIR. Content-based image retrieval (CBIR), additionally called question by image content (QBIC) and content-based visual info retrieval (CBVIR) is that the application of laptop vision techniques to the image retrieval drawback, that is, the matter of checking out digital pictures in giant databases. In this book we have compared classical histogram method for image retrieval with retrieval using Gabor, Wavelet, Complex Wavelet, Radon transform and Ridgelet transform. Image retrieval performance is estimated by using Precession and Recall. 300 pp. Englisch. N° de réf. du vendeur 9783659875298
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ghuge NilamDr. Nilam N. Ghuge has obtained his Ph.D in Electronics Engineering. His area of research is Image Processing and Retrieval and Pattern Recognition. He has published papers in various journals like Elsevier, Springer, IEEE. N° de réf. du vendeur 158124893
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 300 pages. 8.66x5.91x0.68 inches. In Stock. N° de réf. du vendeur 3659875295
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In CBIR the most common feature used are shape, colors, texture etc. To improve the accuracy of retrieval, it must look on the far side the classical features. The features which could easily be extracted from data could be considered. One of such feature is directionality of the image texture. Directional information can be represented in a compact manner by using transform like wavelet, Gabor, Radon etc. In this book we address this problem of using directional information to increase accuracy of CBIR. Content-based image retrieval (CBIR), additionally called question by image content (QBIC) and content-based visual info retrieval (CBVIR) is that the application of laptop vision techniques to the image retrieval drawback, that is, the matter of checking out digital pictures in giant databases. In this book we have compared classical histogram method for image retrieval with retrieval using Gabor, Wavelet, Complex Wavelet, Radon transform and Ridgelet transform. Image retrieval performance is estimated by using Precession and Recall.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 300 pp. Englisch. N° de réf. du vendeur 9783659875298
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. A Novel Approach For Improvements In Content Based Image Retrieval | Nilam Ghuge (u. a.) | Taschenbuch | 300 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659875298 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 103805183
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In CBIR the most common feature used are shape, colors, texture etc. To improve the accuracy of retrieval, it must look on the far side the classical features. The features which could easily be extracted from data could be considered. One of such feature is directionality of the image texture. Directional information can be represented in a compact manner by using transform like wavelet, Gabor, Radon etc. In this book we address this problem of using directional information to increase accuracy of CBIR. Content-based image retrieval (CBIR), additionally called question by image content (QBIC) and content-based visual info retrieval (CBVIR) is that the application of laptop vision techniques to the image retrieval drawback, that is, the matter of checking out digital pictures in giant databases. In this book we have compared classical histogram method for image retrieval with retrieval using Gabor, Wavelet, Complex Wavelet, Radon transform and Ridgelet transform. Image retrieval performance is estimated by using Precession and Recall. N° de réf. du vendeur 9783659875298
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Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA82936598752956
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