Communications - Scientific Letters of the University of Zilina 2013, 15(11):55-59 | DOI: 10.26552/com.C.2013.2A.55-59

Novel Approach to Color Texture Retrieval Based on GLCM

Miroslav Benco1, Robert Hudec1, Martina Zachariasova1, Patrik Kamencay1, Slavomir Matuska1
1 Department of Telecommunications, Faculty of Electrotechnical Engineering, University of Zilina, Slovakia

The color and texture are very important features in image analysis. In this paper, the combination of these features is presented. Several approaches for color texture features extraction are researched. The improvement of the one-dimensional version of GLCM (Gray Level Co-occurrence Matrix) for color textures was designed. We named this method as Color Level Co-occurrence Matrix (1D-CLCM). The experiments on database of 2600 color images are provided. Finally, the evaluation and comparison of image retrieval results for separate methods are presented.

Keywords: co-occurrence, color texture, GLCM, one-dimensional, texture extraction

Published: July 31, 2013  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Benco, M., Hudec, R., Zachariasova, M., Kamencay, P., & Matuska, S. (2013). Novel Approach to Color Texture Retrieval Based on GLCM. Communications - Scientific Letters of the University of Zilina, 15(2A), 55-59. doi: 10.26552/com.C.2013.2A.55-59
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. ASKOY, S., HARALIC, R., M.: Using Texture in Image Similarity and Retrieval, Texture Analysis in Machine Vision, M. Pietikainen, Ed., World Scientific, Singapore, vol. 20, pp. 129-149, 2000. Go to original source...
    2. PASCHOS, G.: Perceptually Uniform Color Spaces for Color Texture Analysis: an Empirical Evaluation, Image Processing, IEEE Transactions, vol. 10, No. 6, pp. 932-937, 2001, doi: 10.1109/83.923289. Go to original source...
    3. MEI, Y., ANDROUTSOS, D.: Color Texture Retrieval Using Wavelet Decomposition on the Hue/Saturation Plane, Multimedia and Expo, 2008 IEEE Intern. Conference, pp.877-880, 2008.
    4. ASSEFAA, D., MANSINHAB, L., TIAMPOB, K. F., RASMUSSENC, H., ABDELLAD, K.: Local Quaternion Fourier Transform and Color Image Texture Analysis, Signal Processing, vol. 90, No. 6, 2010, pp. 1825-1835, ISSN 0165-1684, DOI: 10.1016/j.sigpro 2009.11.031. Go to original source...
    5. MUTASEM, K., S., A., KHAIRUDDIN, B., O., SHAHRUL, A., N., ALMARASHDAH, I.: Fish Recognition Based on Robust Features Extraction from Color Texture Measurements Using Back-propagation Classifier, J. of Theoretical and Applied Information Technology, vol. 18. No. 1, 2010, Paper ID: 1401-JATIT-2K10.
    6. PABAMALIE, L., A., I., PREMARATNE, H., L.: A Grain Quality Classification System, Inter. Conference on Information Society (i-Society), London, pp. 56-61, 2010, ISBN: 978-1-4577-1823-6. Go to original source...
    7. HOSSAIN, K., PAREKH, R.: Extending GLCM to Include Color Information for Texture Recognition, Intern. Conference on Modeling, Optimization and Computing, Book Series: AIP Conference Proc., vol. 1298, pp. 583-588, 2010, DOI: 10.1063/1.3516370, ISSN: 0094-243X, ISBN: 978-0-7354-0854-8. Go to original source...
    8. BENCO, M., HUDEC, R.: Novel Method for Color Texture Features Extraction Based on GLCM, Radioengineering, vol. 16, No. 4, pp. 64-67, ISSN 1210-2512, 2007.
    9. TOU, J., Y., TAY, Y., H., LAU, P., Y.: One-dimensional Grey-level Co-occurrence Matrices for Texture Classification, Information Technology, 2008, ITSim 2008, Intern. Symposium, vol. 3, pp.1-6, 2008. Go to original source...
    10. HARALICK, R., M.: Statistical and Structural Approaches to Texture, Proc. of the IEEE, 67, pp. 786-804, 1979. Go to original source...
    11. HARALICK, R. M.; SHANMUGAM, K.; Dinstein, Its''Hak, "Textural Features for Image Classification," Systems, Man and Cybernetics, IEEE Transactions on, vol. SMC-3, No. 6, pp.610, 621, Nov. 1973, MITMediaLab,Vision texture, VisTexdatabase, http://wwwhite.media.mit.edu/vismod/imagery/VisionTexture/vistex.html, 1995 Go to original source...
    12. MITMediaLab,Vision texture, VisTexdatabase, http://wwwhite.media.mit.edu/vismod/imagery/VisionTexture/vistex.html, (1995)
    13. OJALA T. at al.: Outex-new Framework for Empirical Evaluation of Texture Analysis Algorithms, Proc. of the 16th Intern. Conference on Pattern Recognition, vol. 1, Quebec, 2002, pp. 701-706, http://www.outex.oulu.
    14. ZACHARIASOVA, M., HUDEC, R., BENCO, M., KAMENCAY, P., LUKAC, P., MATUSKA, S.: The Effect of Metric Space on The Results of Graph Based Colour Image Segmentation, Communications - Scientific Letters of the University of Zilina, vol. 14, No. 3, 2012, ISSN 1335-4205. Go to original source...

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content