Edge detection is very important terminology in image processing and for computer vision. Edge detection is in the forefront of image processing for object detection, so it is crucial to have a good understanding of edge detection operators. An improved scheme for contour detection with better performance measure has been proposed in this book with the help of image gradients. A 9x9 Laplacian and Gaussian (LOG) filter has been proposed. The present study has shown that the gradient images obtained by the 9x9 Laplacian and Gaussian (LOG) mask appears to be much clearer with sharp and prominent edges than those obtained through 5x5 Laplacian and Gaussian (LOG) filter and also provides better results than traditional edge detectors. The method has been applied to a number of real life digital images and better performance measure of contour detection has been achieved. Comparative analyses of different edge detection operators in image processing are also presented and discussed. It has been observed that the performance of canny edge detection operator is much better then Sobel, Roberts, Prewitt and Laplacian of Gaussian (LoG) in respect to the image appearance and object boundary.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Edge detection is very important terminology in image processing and for computer vision. Edge detection is in the forefront of image processing for object detection, so it is crucial to have a good understanding of edge detection operators. An improved scheme for contour detection with better performance measure has been proposed in this book with the help of image gradients. A 9x9 Laplacian and Gaussian (LOG) filter has been proposed. The present study has shown that the gradient images obtained by the 9x9 Laplacian and Gaussian (LOG) mask appears to be much clearer with sharp and prominent edges than those obtained through 5x5 Laplacian and Gaussian (LOG) filter and also provides better results than traditional edge detectors. The method has been applied to a number of real life digital images and better performance measure of contour detection has been achieved. Comparative analyses of different edge detection operators in image processing are also presented and discussed. It has been observed that the performance of canny edge detection operator is much better then Sobel, Roberts, Prewitt and Laplacian of Gaussian (LoG) in respect to the image appearance and object boundary. 64 pp. Englisch. Nº de ref. del artículo: 9786203841107
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Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Acharjya Pinaki PratimPinaki Pratim AcharjyaProfessor, Dept, of CSEHaldia Institute of TechnologyHaldia, West BengalEdge detection is very important terminology in image processing and for computer vision. Edge detection is in th. Nº de ref. del artículo: 470574622
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Edge detection is very important terminology in image processing and for computer vision. Edge detection is in the forefront of image processing for object detection, so it is crucial to have a good understanding of edge detection operators. An improved scheme for contour detection with better performance measure has been proposed in this book with the help of image gradients. A 9x9 Laplacian and Gaussian (LOG) filter has been proposed. The present study has shown that the gradient images obtained by the 9x9 Laplacian and Gaussian (LOG) mask appears to be much clearer with sharp and prominent edges than those obtained through 5x5 Laplacian and Gaussian (LOG) filter and also provides better results than traditional edge detectors. The method has been applied to a number of real life digital images and better performance measure of contour detection has been achieved. Comparative analyses of different edge detection operators in image processing are also presented and discussed. It has been observed that the performance of canny edge detection operator is much better then Sobel, Roberts, Prewitt and Laplacian of Gaussian (LoG) in respect to the image appearance and object boundary. Nº de ref. del artículo: 9786203841107
Cantidad disponible: 1 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Edge detection is very important terminology in image processing and for computer vision. Edge detection is in the forefront of image processing for object detection, so it is crucial to have a good understanding of edge detection operators. An improved scheme for contour detection with better performance measure has been proposed in this book with the help of image gradients. A 9x9 Laplacian and Gaussian (LOG) filter has been proposed. The present study has shown that the gradient images obtained by the 9x9 Laplacian and Gaussian (LOG) mask appears to be much clearer with sharp and prominent edges than those obtained through 5x5 Laplacian and Gaussian (LOG) filter and also provides better results than traditional edge detectors. The method has been applied to a number of real life digital images and better performance measure of contour detection has been achieved. Comparative analyses of different edge detection operators in image processing are also presented and discussed. It has been observed that the performance of canny edge detection operator is much better then Sobel, Roberts, Prewitt and Laplacian of Gaussian (LoG) in respect to the image appearance and object boundary.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Nº de ref. del artículo: 9786203841107
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Object Edge Detection Using the Magnitude of the Gradient | Concepts and Techniques | Pinaki Pratim Acharjya (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203841107 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 120023243
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