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» VISTO: A new CBIR system for vector images
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ICIP
2002
IEEE
14 years 10 months ago
Color texture moments for content-based image retrieval
In this paper, we adopt local Fourier transform as a texture representation scheme and derive eight characteristic maps for describing different aspects of co-occurrence relations...
Hui Yu, Mingjing Li, HongJiang Zhang, Jufu Feng
MVA
2000
191views Computer Vision» more  MVA 2000»
13 years 10 months ago
Development of Visual Inspection System Based on Vector Analysis Technique
The present paper proposes a new concept of image processing method based on vector representation for visual inspection test. The method was applied to detect defects and extract...
Masatake Sakuma, Katsumi Kubo, Shigeru Kanemoto, T...
ICIP
2003
IEEE
14 years 2 months ago
Evaluating group-based relevance feedback for content-based image retrieval
We have been developing new relevance feedback algorithms for Content-based Image Retrieval (CBIR) that allow the user to achieve more flexible query. In conjunction with the new...
Munehiro Nakazato, Charlie K. Dagli, Thomas S. Hua...
ECCV
2000
Springer
14 years 10 months ago
Learning Over Multiple Temporal Scales in Image Databases
Abstract. The ability to learn from user interaction is an important asset for content-based image retrieval (CBIR) systems. Over short times scales, it enables the integration of ...
Nuno Vasconcelos, Andrew Lippman
ICDE
2006
IEEE
191views Database» more  ICDE 2006»
14 years 10 months ago
Query Decomposition: A Multiple Neighborhood Approach to Relevance Feedback Processing in Content-based Image Retrieval
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
Kien A. Hua, Ning Yu, Danzhou Liu