Outex - new framework for empirical evaluation of texture analysis algorithms. This paper presents the current status of a new initiative aimed at developing a versatile framework and image database for empirical evaluation of texture analysis algorithms. The proposed Outex framework contains a large collection of surface textures captured under different conditions, which facilitates construction of a wide range of texture analysis problems. The problems are encapsulated into test suites, for which baseline results obtained with algorithms from literature are provided. The rich functionality of the framework is demonstrated with examples in texture classification, segmentation and retrieval. The framework has a web site for public dissemination of the database and comparative results obtained by research groups world wide.

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  1. Aptoula, Erchan; Pham, Minh-Tan; Lefèvre, Sébastien: Quasi-flat zones for angular data simplification (2017)
  2. Căliman, Alexandru; Ivanovici, Mihai; Richard, Noël: Probabilistic pseudo-morphology for grayscale and color images (2014) ioport
  3. Guo, Yimo; Zhao, Guoying; Pietikäinen, Matti: Local configuration features and discriminative learnt features for texture description (2014) ioport
  4. Fernández, Antonio; Álvarez, Marcos X.; Bianconi, Francesco: Texture description through histograms of equivalent patterns (2013)
  5. Maani, Rouzbeh; Kalra, Sanjay; Yang, Yee-Hong: Noise robust rotation invariant features for texture classification (2013) ioport
  6. Porebski, A.; Vandenbroucke, N.; Macaire, L.: Supervised texture classification: color space or texture feature selection? (2013) ioport
  7. Alvarez, Susana; Vanrell, Maria: Texton theory revisited: a bag-of-words approach to combine textons (2012) ioport
  8. Aptoula, Erchan: Extending morphological covariance (2012) ioport
  9. Guo, Yimo; Zhao, Guoying; Pietikäinen, Matti: Discriminative features for texture description (2012) ioport
  10. Zhu, Changren; Wang, Runsheng: Local multiple patterns based multiresolution gray-scale and rotation invariant texture classification (2012) ioport
  11. Ilea, Dana E.; Whelan, Paul F.: Image segmentation based on the integration of colour-texture descriptors -- a review (2011)
  12. Qazi, Imtnan-Ul-Haque; Alata, Olivier; Burie, Jean-Christophe; Moussa, Ahmed; Fernandez-Maloigne, Christine: Choice of a pertinent color space for color texture characterization using parametric spectral analysis (2011)
  13. Qian, Xueming; Hua, Xian-Sheng; Chen, Ping; Ke, Liangjun: PLBP: An effective local binary patterns texture descriptor with pyramid representation (2011) ioport
  14. Guo, Zhenhua; Zhang, Lei; Zhang, David: Rotation invariant texture classification using LBP variance (LBPV) with global matching (2010)
  15. Ilea, Dana E.; Whelan, Paul F.: CTex -- an adaptive unsupervised segmentation algorithm based on color-texture coherence (2008)
  16. Aptoula, E.; Lefèvre, S.: A comparative study on multivariate mathematical morphology (2007)
  17. Bianconi, Francesco; Fernández, Antonio: Evaluation of the effects of Gabor filter parameters on texture classification (2007)
  18. Gelzinis, A.; Verikas, A.; Bacauskiene, M.: Increasing the discrimination power of the co-occurrence matrix-based features (2007)
  19. Toyoda, Takahiro; Hasegawa, Osamu: Extension of higher order local autocorrelation features (2007)
  20. Mäenpää, Topi; Pietikäinen, Matti: Classification with color and texture: Jointly or separately? (2004) ioport

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