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ISBN 10: 6202677074 ISBN 13: 9786202677073
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Image edge detection algorithms using color models | Abhishek Gudipalli (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202677073 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Edge detection is one of the fundamental tasks in image analysis. Proposed research work highlights the detection of edges of each layer separately through Sobel/Laplacian operators and concatenating them with the other layers. This approach gives better results in detecting edges when compared with the existing methods. The original image is transformed to other color models to extract the features effectively. The different color models used in the proposed work are RGB (Red, Green, Blue), YCbCr (Y-Luma, Cb - Blue difference and Cr-Red Difference Chrominance), YUV (Y-Luma, U - Blue difference and V-Red Difference Chrominance) and XYZ (Y-Luminance, Z - Blue difference and X-Red Difference Chrominance).The main concept of proposed research work is to develop an algorithm which is device/machine independent to extract the edge detection features using different color models. 132 pp. Englisch.
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ISBN 10: 6202677074 ISBN 13: 9786202677073
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gudipalli AbhishekDr. Abhishek Gudipalli is currently working as an Assistant Professor Senior in the School of Electrical Engineering, VIT University, Vellore. He has 09 years of teaching experience. He has published many papers in .
Lingua: Inglese
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ISBN 10: 6202677074 ISBN 13: 9786202677073
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Editore: LAP LAMBERT Academic Publishing Aug 2020, 2020
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Edge detection is one of the fundamental tasks in image analysis. Proposed research work highlights the detection of edges of each layer separately through Sobel/Laplacian operators and concatenating them with the other layers. This approach gives better results in detecting edges when compared with the existing methods. The original image is transformed to other color models to extract the features effectively. The different color models used in the proposed work are RGB (Red, Green, Blue), YCbCr (Y-Luma, Cb - Blue difference and Cr-Red Difference Chrominance), YUV (Y-Luma, U - Blue difference and V-Red Difference Chrominance) and XYZ (Y-Luminance, Z - Blue difference and X-Red Difference Chrominance).The main concept of proposed research work is to develop an algorithm which is device/machine independent to extract the edge detection features using different color models.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202677074 ISBN 13: 9786202677073
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Edge detection is one of the fundamental tasks in image analysis. Proposed research work highlights the detection of edges of each layer separately through Sobel/Laplacian operators and concatenating them with the other layers. This approach gives better results in detecting edges when compared with the existing methods. The original image is transformed to other color models to extract the features effectively. The different color models used in the proposed work are RGB (Red, Green, Blue), YCbCr (Y-Luma, Cb - Blue difference and Cr-Red Difference Chrominance), YUV (Y-Luma, U - Blue difference and V-Red Difference Chrominance) and XYZ (Y-Luminance, Z - Blue difference and X-Red Difference Chrominance).The main concept of proposed research work is to develop an algorithm which is device/machine independent to extract the edge detection features using different color models.