Perceptual texture retrieval using spatial distributions of textons (SDoT)

Xinghui Dong, Junyu Dong, Shengke Wang, Michael John Chantler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

It has been shown that the spatial information of local image characteristics is important to human perception and computational features. Inspired by these studies, we propose a set of new computational texture features based on the spatial distributions of textons (SDoT). First, gradient magnitude and gradient direction spectra are computed from a texture image. Second, the multiple gradient spectra simultaneous autoregressive (MGSSAR) models are estimated for each image. Both model coefficients and the variance of the model estimation error jointly construct a local feature space. Third, &-means is used to learn textons from the local features. All textons learned from a texture database are combined into a dictionary. Fourth, vector quantization is utilized to map a texture from the local feature space into the texton space. Finally, an aura matrix is computed from the texton map of each texture in order to encode the spatial distributions of the textons. The results of a perceptual texture retrieval experiment show that the proposed feature set performs more consistently with human observers than 56 existing feature sets. We attribute this to the fact that the proposed feature set encodes the spatial information of textons.

Original languageEnglish
Title of host publication2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)
PublisherIEEE
Pages663-666
Number of pages4
ISBN (Electronic)9789881476807
DOIs
Publication statusPublished - 25 Feb 2016
Event2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2015 - Hong Kong, Hong Kong
Duration: 16 Dec 201519 Dec 2015

Conference

Conference2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2015
CountryHong Kong
CityHong Kong
Period16/12/1519/12/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Modelling and Simulation
  • Signal Processing

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  • Cite this

    Dong, X., Dong, J., Wang, S., & Chantler, M. J. (2016). Perceptual texture retrieval using spatial distributions of textons (SDoT). In 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA) (pp. 663-666). IEEE. https://doi.org/10.1109/APSIPA.2015.7415353