Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture based medical image indexing and retrieval: application to cardiac imaging
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Is It Time for a Moratorium on Metadata?
IEEE MultiMedia
Bidimensional empirical mode decomposition modified for texture analysis
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
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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.