2003
DOI: 10.1016/s0031-3203(03)00171-7
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SASI: a generic texture descriptor for image retrieval

Abstract: In this paper, a generic texture descriptor, namely, Statistical Analysis of Structural Information (SASI) is introduced as a representation of texture. SASI is based on statistics of clique autocorrelation coefficients, calculated over structuring windows. SASI defines a set of clique windows to extract and measure various structural properties of texture by using a spatial multi-resolution method. Experimental results, performed on various image databases, indicate that SASI is more successful then the Gabor… Show more

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Cited by 39 publications
(24 citation statements)
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“…These classifiers are learned using images from LFW database. We showed performance in line with recent attribute classifiers from the literature and important texture descriptors such as SASI (Çarkacıoglu and Yarman-Vural, 2003).…”
Section: Resultssupporting
confidence: 83%
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“…These classifiers are learned using images from LFW database. We showed performance in line with recent attribute classifiers from the literature and important texture descriptors such as SASI (Çarkacıoglu and Yarman-Vural, 2003).…”
Section: Resultssupporting
confidence: 83%
“…Finally, given a multiple-attribute query, we use some fusion methods to combine the outputs of the classifiers generating a reduced list of people complying with the describable attributes given by the user. With the visual dictionaries introduction, we achieve significant improvements on the results in comparison to the results obtained in the state of the art , our own prior work (Fabian et al, 2012), and also a top-performer texture descriptor in the literature (Çarkacıoglu and Yarman-Vural, 2003;Penatti et al, 2012).…”
Section: Introductionmentioning
confidence: 88%
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“…(SASI) [19] Algorithm for texture descriptor is used to extract texture information from IM. The main advantage of using SASI is its capability of capturing small granularities and discontinuities in texture pattern.…”
Section: A Sasi: Statistical Analysis Of Structural Informationmentioning
confidence: 99%
“…This is the retrieval of images on the basis of features automatically derived from the images themselves. The features most widely used are texture [1][2][3], color [4][5][6] and shape [7][8][9]. A plethora of texture features extraction algorithms exists, such as wavelets [10][11][12], mathematical morphology [13] and stochastic models [14], to mention few.…”
Section: Introductionmentioning
confidence: 99%