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JDCTA
2010
170views more  JDCTA 2010»
13 years 3 days ago
Color and Texture Feature For Content Based Image Retrieval
Content based image retrieval (CBIR) has been one of the most important research areas in computer science for the last decade. A retrieval method which combines color and texture...
Jianhua Wu, Zhaorong Wei, Youli Chang
CIVR
2004
Springer
213views Image Analysis» more  CIVR 2004»
13 years 10 months ago
Evaluation of Texture Features for Content-Based Image Retrieval
Abstract. We have carried out a detailed evaluation of the use of texture features in a query-by-example approach to image retrieval. We used 3 radically different texture feature...
Peter Howarth, Stefan M. Rüger
SIBGRAPI
2003
IEEE
13 years 10 months ago
Using Efficient Visual Exploration Techniques to Evaluate Features for Content-Based Image Retrieval
This paper presents a novel visual approach to evaluate, in a fast and effective way, the development of new image feature extraction techniques concerning content-based image ret...
José Fernando Rodrigues Jr., César A...
ICPR
2000
IEEE
14 years 6 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
CLEF
2005
Springer
13 years 11 months ago
Content-Based Retrieval of Medical Images by Combining Global Features
A combination of several classifiers using global features for the content description of medical images is proposed. Beside well known texture histogram features, downscaled repr...
Mark Oliver Güld, Christian Thies, Benedikt F...