Feature Extraction and Classification Methods of Texture Images: Performance Analysis of Feature Extraction Methods Under Different Classifiers - Brossura
Sinossi
In texture classification the goal is to assign an unknown sample texture image to one of a set of known texture classes.Important applications include industrial and bio medical surface inspection, for example for defects and disease, ground classification and segmentation of satellite or aerial imagery, segmentation of textured regions in document analysis, and content-based access to image databases. However, despite many potential areas of application for texture analysis in industry there is only a limited number of successful examples. A major problem is that textures in the real world are often not uniform, due to changes in orientation, scale or other visual appearance. In addition, the degree of computational complexity of many of the proposed texture measures is very high.A wide variety of techniques for describing image texture have been proposed in literature. This work is an analysis of texture image classification in different classifier under two different features called wavelet and statistical. The result shows that image classification with wavelet feature and feed forward neural network gives better result.
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L'autore
Asst. Professor of Computer Science & Engg. Department at Mody Institute of Technology & Science Laxmangarh, India. He has graduated from CCS University Meerut and Post graduated from AAI Deemed University Allahabad, and pursuing Phd. From MITS university, Laxmangarh, India. He has many publications books and research work.
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Feature Extraction and Classification Methods of Texture Images
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LAP LAMBERT Academic Publishing Jul 2013, 2013
ISBN 10: 3659417394
ISBN 13: 9783659417399
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In texture classification the goal is to assign an unknown sample texture image to one of a set of known texture classes.Important applications include industrial and bio medical surface inspection, for example for defects and disease, ground classification and segmentation of satellite or aerial imagery, segmentation of textured regions in document analysis, and content-based access to image databases. However, despite many potential areas of application for texture analysis in industry there is only a limited number of successful examples. A major problem is that textures in the real world are often not uniform, due to changes in orientation, scale or other visual appearance. In addition, the degree of computational complexity of many of the proposed texture measures is very high.A wide variety of techniques for describing image texture have been proposed in literature. This work is an analysis of texture image classification in different classifier under two different features called wavelet and statistical. The result shows that image classification with wavelet feature and feed forward neural network gives better result. 96 pp. Englisch. Codice articolo 9783659417399
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Feature Extraction and Classification Methods of Texture Images
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Feature Extraction and Classification Methods of Texture Images
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
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Feature Extraction and Classification Methods of Texture Images
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ISBN 10: 3659417394
ISBN 13: 9783659417399
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh Ajay KumarAsst. Professor of Computer Science & Engg. Department at Mody Institute of Technology & Science Laxmangarh, India. He has graduated from CCS University Meerut and Post graduated from AAI Deemed University Allahabad, . Codice articolo 5154949
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Feature Extraction and Classification Methods of Texture Images
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
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Feature Extraction and Classification Methods of Texture Images : Performance Analysis of Feature Extraction Methods Under Different Classifiers
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In texture classification the goal is to assign an unknown sample texture image to one of a set of known texture classes.Important applications include industrial and bio medical surface inspection, for example for defects and disease, ground classification and segmentation of satellite or aerial imagery, segmentation of textured regions in document analysis, and content-based access to image databases. However, despite many potential areas of application for texture analysis in industry there is only a limited number of successful examples. A major problem is that textures in the real world are often not uniform, due to changes in orientation, scale or other visual appearance. In addition, the degree of computational complexity of many of the proposed texture measures is very high.A wide variety of techniques for describing image texture have been proposed in literature. This work is an analysis of texture image classification in different classifier under two different features called wavelet and statistical. The result shows that image classification with wavelet feature and feed forward neural network gives better result. Codice articolo 9783659417399
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Feature Extraction and Classification Methods of Texture Images | Performance Analysis of Feature Extraction Methods Under Different Classifiers
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LAP LAMBERT Academic Publishing, 2013
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Taschenbuch. Condizione: Neu. Feature Extraction and Classification Methods of Texture Images | Performance Analysis of Feature Extraction Methods Under Different Classifiers | Ajay Kumar Singh (u. a.) | Taschenbuch | 96 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659417399 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 105748614
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Feature Extraction and Classification Methods of Texture Images
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LAP LAMBERT Academic Publishing Jul 2013, 2013
ISBN 10: 3659417394
ISBN 13: 9783659417399
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In texture classification the goal is to assign an unknown sample texture image to one of a set of known texture classes.Important applications include industrial and bio medical surface inspection, for example for defects and disease, ground classification and segmentation of satellite or aerial imagery, segmentation of textured regions in document analysis, and content-based access to image databases. However, despite many potential areas of application for texture analysis in industry there is only a limited number of successful examples. A major problem is that textures in the real world are often not uniform, due to changes in orientation, scale or other visual appearance. In addition, the degree of computational complexity of many of the proposed texture measures is very high.A wide variety of techniques for describing image texture have been proposed in literature. This work is an analysis of texture image classification in different classifier under two different features called wavelet and statistical. The result shows that image classification with wavelet feature and feed forward neural network gives better result.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch. Codice articolo 9783659417399
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Feature Extraction and Classification Methods of Texture Images: Performance Analysis of Feature Extraction Methods Under Different Classifiers
Editore:
LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659417394
ISBN 13: 9783659417399
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