Paper Info
Title
Mapping perceptual texture similarity for image retrieval
Abstract
Images are being produced and made available in ever increasing numbers; but how can we find images “like this one” that are of interest to us? Many different systems have been developed which offer content-based image retrieval (CBIR), using low-level features such as colour, texture and shape; but how can the retrieval performance of such systems be measured? We have produced a perceptually-derived ranking of similar images using the Brodatz textures image dataset, based on a human study, which can be used to benchmark retrieval performance. In this paper, we show how a “mental map” may be derived from individual judgements to provide a scale of psychological distance, and a visual indication of image similarity.
Year
DOI
Venue
2005
10.1007/11499145_97
SCIA
Keywords
Field
DocType
similar image,different system,retrieval performance,human study,benchmark retrieval performance,brodatz textures image dataset,perceptual texture similarity,low-level feature,image similarity,content-based image retrieval,individual judgement,image retrieval
Computer vision,Similitude,Automatic image annotation,Pattern recognition,Ranking,Image texture,Computer science,Image retrieval,Image processing,Artificial intelligence,Perception,Visual Word
Conference
Volume
ISSN
ISBN
3540
0302-9743
3-540-26320-9
Citations 
PageRank 
References 
0
0.34
5
Authors
2
Name
Order
Citations
PageRank
Janet S. Payne1151.70
John Stonham2303.63