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Content-based image retrieval uses features at a low or pixel image level for such color, texture and shape. And on the basis of this feature get the right photos from storage media. But here the key problem for the researcher is to find the most relevant image from the database first or for a small amount of search iteration. In the short term the HSV color histogram is an excellent feature of the image and has been used in various investigative programs. In this article, the HSV Color histogram is based on an image to extract a color element and measure the value of the histogram by 72 different barrels. The stitching element is removed using a discrete wavelet transform that helps to remove the intricate pattern pattern present in the image. The definition of a histogram feature is used to determine the location and geometric details of an image by subtracting the edges present in the image and combining these elements into a single element vector so that it can properly enlarge the image. In the process of classifying the vector classifier machine is used to classify images into different categories accordingly.
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Design and analysis of an efficient image retrieval technique
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LAP LAMBERT Academic Publishing Mai 2021, 2021
ISBN 10: 6203861936
ISBN 13: 9786203861938
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Content-based image retrieval uses features at a low or pixel image level for such color, texture and shape. And on the basis of this feature get the right photos from storage media. But here the key problem for the researcher is to find the most relevant image from the database first or for a small amount of search iteration. In the short term the HSV color histogram is an excellent feature of the image and has been used in various investigative programs. In this article, the HSV Color histogram is based on an image to extract a color element and measure the value of the histogram by 72 different barrels. The stitching element is removed using a discrete wavelet transform that helps to remove the intricate pattern pattern present in the image. The definition of a histogram feature is used to determine the location and geometric details of an image by subtracting the edges present in the image and combining these elements into a single element vector so that it can properly enlarge the image. In the process of classifying the vector classifier machine is used to classify images into different categories accordingly. 92 pp. Englisch. Codice articolo 9786203861938
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Design and analysis of an efficient image retrieval technique
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ISBN 10: 6203861936
ISBN 13: 9786203861938
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ansari Mohd. AquibMohd. Aquib Ansari has completed his B.E. from SATI Vidisha in Information Technology (2014). He has done his M.Tech. from MITS Gwalior in Information Technology (2017). He is currently pursuing his Ph.D. from MNNIT. Codice articolo 490749334
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Design and analysis of an efficient image retrieval technique
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LAP LAMBERT Academic Publishing Mai 2021, 2021
ISBN 10: 6203861936
ISBN 13: 9786203861938
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Taschenbuch. Condizione: Neu. Neuware -Content-based image retrieval uses features at a low or pixel image level for such color, texture and shape. And on the basis of this feature get the right photos from storage media. But here the key problem for the researcher is to find the most relevant image from the database first or for a small amount of search iteration. In the short term the HSV color histogram is an excellent feature of the image and has been used in various investigative programs. In this article, the HSV Color histogram is based on an image to extract a color element and measure the value of the histogram by 72 different barrels. The stitching element is removed using a discrete wavelet transform that helps to remove the intricate pattern pattern present in the image. The definition of a histogram feature is used to determine the location and geometric details of an image by subtracting the edges present in the image and combining these elements into a single element vector so that it can properly enlarge the image. In the process of classifying the vector classifier machine is used to classify images into different categories accordingly.Books on Demand GmbH, Überseering 33, 22297 Hamburg 92 pp. Englisch. Codice articolo 9786203861938
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Design and analysis of an efficient image retrieval technique
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LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203861936
ISBN 13: 9786203861938
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Content-based image retrieval uses features at a low or pixel image level for such color, texture and shape. And on the basis of this feature get the right photos from storage media. But here the key problem for the researcher is to find the most relevant image from the database first or for a small amount of search iteration. In the short term the HSV color histogram is an excellent feature of the image and has been used in various investigative programs. In this article, the HSV Color histogram is based on an image to extract a color element and measure the value of the histogram by 72 different barrels. The stitching element is removed using a discrete wavelet transform that helps to remove the intricate pattern pattern present in the image. The definition of a histogram feature is used to determine the location and geometric details of an image by subtracting the edges present in the image and combining these elements into a single element vector so that it can properly enlarge the image. In the process of classifying the vector classifier machine is used to classify images into different categories accordingly. Codice articolo 9786203861938
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Design and analysis of an efficient image retrieval technique
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ISBN 13: 9786203861938
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Taschenbuch. Condizione: Neu. Design and analysis of an efficient image retrieval technique | Mohd. Aquib Ansari (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203861938 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Codice articolo 120378915
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