An Image Retrieval with Color and Texture Features of Image Sub-Blocks (Paperback)
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An Image Retrieval with Color and Texture Features of Image Sub-Blocks (Paperback) (2014)
DE PB NW RP
ISBN: 9783639713244 bzw. 3639713249, in Deutsch, Scholars Press, United States, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, The Book Depository EURO [60485773], London, United Kingdom.
Language: English Brand New Book ***** Print on Demand *****.Each image is partitioned into 4×6 grids of equal-sized sub-blocks. The size of the sub-block is maintained as 64x64 pixels. Further the size of the sub-block is fixed for all the images. Then the color and texture features of each sub-block are computed. A color feature descriptor Local AutoCorrelogram (LAC) which is invariant to translation and occlusion is proposed to represent the color of the sub-block. Similarly, the texture of the sub-block is extracted based on Edge Oriented Gray Tone Spatial Dependency Matrix (EOGTSDM) of an image. An image matching scheme based on Integrated Minimum Cost Sub-block Matching (IMCSM) principle is used to compare the query and the target image, which in turn reduces the cost of finding the integrated matching distance. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image, which is used for matching the images. To further improve the quality of retrieval, a Relevance Feedback approach based on a feature re-weighting scheme is used to improve the retrieval accuracy. The experimental results show that this method has improved retrieval precision and recall.
Language: English Brand New Book ***** Print on Demand *****.Each image is partitioned into 4×6 grids of equal-sized sub-blocks. The size of the sub-block is maintained as 64x64 pixels. Further the size of the sub-block is fixed for all the images. Then the color and texture features of each sub-block are computed. A color feature descriptor Local AutoCorrelogram (LAC) which is invariant to translation and occlusion is proposed to represent the color of the sub-block. Similarly, the texture of the sub-block is extracted based on Edge Oriented Gray Tone Spatial Dependency Matrix (EOGTSDM) of an image. An image matching scheme based on Integrated Minimum Cost Sub-block Matching (IMCSM) principle is used to compare the query and the target image, which in turn reduces the cost of finding the integrated matching distance. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image, which is used for matching the images. To further improve the quality of retrieval, a Relevance Feedback approach based on a feature re-weighting scheme is used to improve the retrieval accuracy. The experimental results show that this method has improved retrieval precision and recall.
2
An image retrieval with color and texture features of image sub-blocks (2014)
EN PB NW
ISBN: 9783639713244 bzw. 3639713249, in Englisch, 168 Seiten, Scholars' Press, Taschenbuch, neu.
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Von Händler/Antiquariat, SuperBookDeals-.
Each image is partitioned into 4×6 grids of equal-sized sub-blocks. The size of the sub-block is maintained as 64x64 pixels. Further the size of the sub-block is fixed for all the images. Then the color and texture features of each sub-block are computed. A color feature descriptor Local AutoCorrelogram (LAC) which is invariant to translation and occlusion is proposed to represent the color of the sub-block. Similarly, the texture of the sub-block is extracted based on Edge Oriented Gray Tone Spatial Dependency Matrix (EOGTSDM) of an image. An image matching scheme based on Integrated Minimum Cost Sub-block Matching (IMCSM) principle is used to compare the query and the target image, which in turn reduces the cost of finding the integrated matching distance. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image, which is used for matching the images. To further improve the quality of retrieval, a Relevance Feedback approach based on a feature re-weighting scheme is used to improve the retrieval accuracy. The experimental results show that this method has improved retrieval precision and recall. Paperback, Label: Scholars' Press, Scholars' Press, Produktgruppe: Book, Publiziert: 2014-03-18, Freigegeben: 2014-03-18, Studio: Scholars' Press, Verkaufsrang: 7741805.
Von Händler/Antiquariat, SuperBookDeals-.
Each image is partitioned into 4×6 grids of equal-sized sub-blocks. The size of the sub-block is maintained as 64x64 pixels. Further the size of the sub-block is fixed for all the images. Then the color and texture features of each sub-block are computed. A color feature descriptor Local AutoCorrelogram (LAC) which is invariant to translation and occlusion is proposed to represent the color of the sub-block. Similarly, the texture of the sub-block is extracted based on Edge Oriented Gray Tone Spatial Dependency Matrix (EOGTSDM) of an image. An image matching scheme based on Integrated Minimum Cost Sub-block Matching (IMCSM) principle is used to compare the query and the target image, which in turn reduces the cost of finding the integrated matching distance. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image, which is used for matching the images. To further improve the quality of retrieval, a Relevance Feedback approach based on a feature re-weighting scheme is used to improve the retrieval accuracy. The experimental results show that this method has improved retrieval precision and recall. Paperback, Label: Scholars' Press, Scholars' Press, Produktgruppe: Book, Publiziert: 2014-03-18, Freigegeben: 2014-03-18, Studio: Scholars' Press, Verkaufsrang: 7741805.
3
Symbolbild
An Image Retrieval with Color and Texture Features of Image Sub-Blocks
DE PB NW RP
ISBN: 9783639713244 bzw. 3639713249, in Deutsch, Scholars' Press, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, THE SAINT BOOKSTORE [51194787], Southport, United Kingdom.
BRAND NEW PRINT ON DEMAND., An Image Retrieval with Color and Texture Features of Image Sub-Blocks, Chaduvula Kavitha.
BRAND NEW PRINT ON DEMAND., An Image Retrieval with Color and Texture Features of Image Sub-Blocks, Chaduvula Kavitha.
4
Symbolbild
An image retrieval with color and texture features of image sub-blocks (2014)
DE PB NW RP
ISBN: 9783639713244 bzw. 3639713249, in Deutsch, Scholars' Press, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
This item is printed on demand for shipment within 3 working days.
This item is printed on demand for shipment within 3 working days.
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