A Parametric Spectral Model for Texture-Based Salience

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9358)

Abstract

We present a novel saliency mechanism based on texture. Local texture at each pixel is characterised by the 2D spectrum obtained from oriented Gabor filters. We then apply a parametric model and describe the texture at each pixel by a combination of two 1D Gaussian approximations. This results in a simple model which consists of only four parameters. These four parameters are then used as feature channels and standard Difference-of-Gaussian blob detection is applied in order to detect salient areas in the image, similar to the Itti and Koch model. Finally, a diffusion process is used to sharpen the resulting regions. Evaluation on a large saliency dataset shows a significant improvement of our method over the baseline Itti and Koch model.

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Notes

Acknowledgements

This work was supported by the EU under the FP-7 grant ICT-2009.2.1-270247 NeuralDynamics and by the FCT under the grants LarSYS UID/EEA/50009/2013 and SparseCoding EXPL/EEI-SII/1982/2013.

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Copyright information

© Springer International Publishing Switzerland 2015

Open Access This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Authors and Affiliations

  • Kasim Terzić
    • 1
  • Sai Krishna
    • 1
  • J. M. H. du Buf
    • 1
  1. 1.Vision Laboratory/LARSysUniversity of the AlgarveFaroPortugal

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