Image Processing: Texture Segmentation Using Multichannel Filtering And Kohonen’s Self Organizing Map - Couverture souple
Synopsis
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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Image Processing
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LAP LAMBERT Academic Publishing Sep 2012, 2012
ISBN 10 : 3659255149
ISBN 13 : 9783659255144
Neuf
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783659255144
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Image Processing: Texture Segmentation Using Multichannel Filtering And Kohonen S Self Organizing Map
Edité par
Lap Lambert Academic Publishing, 2012
ISBN 10 : 3659255149
ISBN 13 : 9783659255144
Neuf
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Paperback. Etat : Brand New. 72 pages. 8.66x5.91x0.17 inches. In Stock. N° de réf. du vendeur 3659255149
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Image Processing
Edité par
LAP LAMBERT Academic Publishing Sep 2012, 2012
ISBN 10 : 3659255149
ISBN 13 : 9783659255144
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783659255144
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Image Processing : Texture Segmentation Using Multichannel Filtering And Kohonen¿s Self Organizing Map
Edité par
LAP LAMBERT Academic Publishing, 2012
ISBN 10 : 3659255149
ISBN 13 : 9783659255144
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783659255144
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