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» Features for image retrieval: an experimental comparison
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ICIP
2002
IEEE
14 years 9 months ago
Content-based image retrieval using stochastic paintbrush transformation
Herein, we propose a new content based image retrieval method. The novelty of our approach lies in the applied image similarity measure : Unlike traditional features like color, t...
Zoltan Kato, Xiaowen Ji, Tamas Sziranyi, Zoltan To...
ESWA
2008
127views more  ESWA 2008»
13 years 7 months ago
A two-level relevance feedback mechanism for image retrieval
Content-based image retrieval (CBIR) is a group of techniques that analyzes the visual features (such as color, shape, texture) of an example image or image subregion to find simi...
Pei-Cheng Cheng, Been-Chian Chien, Hao-Ren Ke, Wei...
IJCAI
2007
13 years 8 months ago
Logistic Regression Models for a Fast CBIR Method Based on Feature Selection
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
Riadh Ksantini, Djemel Ziou, Bernard Colin, Fran&c...
COMPSAC
2002
IEEE
14 years 11 days ago
An Effective Content-Based Visual Image Retrieval System
In this paper, an effective content-based visual image retrieval system is presented. This system consists of two main components: visual content extraction and indexing, and quer...
Xiuqi Li, Shu-Ching Chen, Mei-Ling Shyu, Borko Fur...
BMVC
2001
13 years 9 months ago
Spectral and Spatial Invariant Image Retrieval using Scene Structural Matrix
We introduce Scene Structural Matrix (SSM), a novel image content descriptor and its application to invariant image retrieval. The SSM captures the overall structural characterist...
Guoping Qiu, S. Sudirman