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» Feature selection for content-based image retrieval
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ICMCS
2008
IEEE
152views Multimedia» more  ICMCS 2008»
14 years 2 months ago
A geometric method to compute directionality features for texture images
In content based image analysis and retrieval, texture feature is an essential component due to its strong discriminative power. Directionality is one of the most significant text...
Md. Monirul Islam, Dengsheng Zhang, Guojun Lu
ICIP
2002
IEEE
14 years 9 months ago
Segmentation and histogram generation using the HSV color space for image retrieval
We have analyzed the properties of the HSV (Hue, Saturation and Value) color space with emphasis on the visual perception of the variation in Hue, Saturation and Intensity values ...
Shamik Sural, Gang Qian, Sakti Pramanik
GIS
2009
ACM
13 years 11 months ago
Classification of raster maps for automatic feature extraction
Raster maps are widely available and contain useful geographic features such as labels and road lines. To extract the geographic features, most research work relies on a manual st...
Yao-Yi Chiang, Craig A. Knoblock
ICPR
2004
IEEE
14 years 8 months ago
Image and Feature Co-Clustering
The visual appearance of an image is closely associated with its low-level features. Identifying the set of features that best characterizes the image is useful for tasks such as ...
Guoping Qiu
CBMS
2009
IEEE
14 years 2 months ago
Comparative study of spine vertebra shape retrieval using learning-based feature selection
Feature extraction and selection are two important steps for shape retrieval. Given a data set, a set of features which describe the shape property from different aspects are extr...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...