Paper Info
Title
Colour-based relevance feedback for image retrieval
Abstract
Colour is an important attribute for image matching and retrieval, and relevance feedback (RF) has been found to improve the retrieval effectiveness in information retrieval systems significantly. We propose a new approach for colour-based RF for image retrieval. The approach makes use of the Multi-Interval Discretization Algorithm to discretize the range of colour histogram values into discrete colour intervals. The probabilistic 0.5 formula is adapted to identify significant colour intervals which are then used to refine the initial query. In addition, knowledge is extracted from the relevance judgement information and represented as a colour interval decision tree. The decision tree is used to aid in classifying the images, retrieved using the modified query in subsequent retrieval, into the relevant and non-relevant sets. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of our proposed RF approach
Year
DOI
Venue
1998
10.1109/MMDBMS.1998.709521
IW-MMDBMS
Keywords
Field
DocType
multimedia computing,image matching,query refinement,trees (mathematics),visual databases,colour-based relevance feedback,probabilistic formula,image classification,discrete colour intervals,image retrieval,colour histogram values,colour interval decision tree,relevance feedback,large image collection,multi-interval discretization algorithm,information retrieval systems,retrieval effectiveness,query processing,image colour analysis,feedback,radio frequency,decision tree,decision trees,information retrieval,data mining,histograms,information retrieval system
Decision tree,Histogram,Automatic image annotation,Relevance feedback,Pattern recognition,Image texture,Computer science,Image retrieval,Artificial intelligence,Contextual image classification,Visual Word
Conference
ISBN
Citations 
PageRank 
0-8186-8676-6
6
0.74
References 
Authors
14
2
Name
Order
Citations
PageRank
Wai-chee Low160.74
Tat-Seng Chua211749653.09