Computational perceptual features for texture representation and retrieval

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Noureddine Abbadeni

Abstract

A perception-based approach to content-based image representation and retrieval is proposed in this paper. We consider textured images and propose to model their textural content by a set of features having a perceptual meaning and their application to content-based image retrieval. We present a new method to estimate a set of perceptual textural features, namely coarseness, directionality, contrast, and busyness. The proposed computational measures can be based upon two representations: the original images representation and the autocorrelation function (associated with original images) representation. The set of computational measures proposed is applied to content-based image retrieval on a large image data set, the well-known Brodatz database. Experimental results and benchmarking show interesting performance of our approach. First, the correspondence of the proposed computational measures to human judgments is shown using a psychometric method based upon the Spearman rank-correlation coefficient. Second, the application of the proposed computational measures in texture retrieval shows interesting results, especially when using results fusion returned by each of the two representations. Comparison is also given with related...Continue Reading

References

Apr 1, 1975·Scientific American·B Julesz
May 26, 1988·Nature·J R Bergen, E H Adelson
Feb 5, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Minh N Do, Martin Vetterli

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Citations

Feb 6, 2014·Cytoskeleton·Wenhua Liu, Evelyn Ralston
Oct 11, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Mohand Saïd Allili
Oct 11, 2012·PloS One·Zhengli ZhuYingkun Hou

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