The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture Applications include industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this book, we study two stage of feature extraction technique using multichannel filter and self-organizing map. Firstly we study channel filters, also known as 2-D Gabor functions. The texture features are extracted using a multichannel approach. The channels comprise of a set of Gabor filters having different sizes, orientations, and frequencies to constitute feature vector. This feature vectors are then given to Self Organizing map for feature reduction.It is shown that the disadvantage of using Gabor filters in texture analysis, namely, the higher dimensionality of the Gaboriau feature space, is overcome by the reduction in the dimensionality of the feature space achieved by SOM.
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The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture Applications include industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this book, we study two stage of feature extraction technique using multichannel filter and self-organizing map. Firstly we study channel filters, also known as 2-D Gabor functions. The texture features are extracted using a multichannel approach. The channels comprise of a set of Gabor filters having different sizes, orientations, and frequencies to constitute feature vector. This feature vectors are then given to Self Organizing map for feature reduction.It is shown that the disadvantage of using Gabor filters in texture analysis, namely, the higher dimensionality of the Gaboriau feature space, is overcome by the reduction in the dimensionality of the feature space achieved by SOM.
Meenakshi Pramanik received B.Tech from M.G.M College of Engg in 2009 and M.Tech (2011) from S.G.G.S.I.E&T College, Maharashtra in Electronics and Telecommunications.Currently she is working as a Programmer Analyst in Cognizant Technology Solutions
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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 -The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture Applications include industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this book, we study two stage of feature extraction technique using multichannel filter and self-organizing map. Firstly we study channel filters, also known as 2-D Gabor functions. The texture features are extracted using a multichannel approach. The channels comprise of a set of Gabor filters having different sizes, orientations, and frequencies to constitute feature vector. This feature vectors are then given to Self Organizing map for feature reduction.It is shown that the disadvantage of using Gabor filters in texture analysis, namely, the higher dimensionality of the Gaboriau feature space, is overcome by the reduction in the dimensionality of the feature space achieved by SOM. 72 pp. Englisch. Nº de ref. del artículo: 9783659255144
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Librería: Revaluation Books, Exeter, Reino Unido
Paperback. Condición: Brand New. 72 pages. 8.66x5.91x0.17 inches. In Stock. Nº de ref. del artículo: 3659255149
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture Applications include industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this book, we study two stage of feature extraction technique using multichannel filter and self-organizing map. Firstly we study channel filters, also known as 2-D Gabor functions. The texture features are extracted using a multichannel approach. The channels comprise of a set of Gabor filters having different sizes, orientations, and frequencies to constitute feature vector. This feature vectors are then given to Self Organizing map for feature reduction.It is shown that the disadvantage of using Gabor filters in texture analysis, namely, the higher dimensionality of the Gaboriau feature space, is overcome by the reduction in the dimensionality of the feature space achieved by SOM.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. Nº de ref. del artículo: 9783659255144
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture Applications include industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this book, we study two stage of feature extraction technique using multichannel filter and self-organizing map. Firstly we study channel filters, also known as 2-D Gabor functions. The texture features are extracted using a multichannel approach. The channels comprise of a set of Gabor filters having different sizes, orientations, and frequencies to constitute feature vector. This feature vectors are then given to Self Organizing map for feature reduction.It is shown that the disadvantage of using Gabor filters in texture analysis, namely, the higher dimensionality of the Gaboriau feature space, is overcome by the reduction in the dimensionality of the feature space achieved by SOM. Nº de ref. del artículo: 9783659255144
Cantidad disponible: 1 disponibles