Multi-Scale Local Spatial Binary Patterns for Content-Based Image Retrieval

  • Yu Xia
  • Shouhong Wan
  • Peiquan Jin
  • Lihua Yue
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)


Content-based image retrieval (CBIR) has been widely studied in recent years. CBIR usually employs feature descriptors to describe the concerned characters of images, such as geometric descriptor and texture descriptor. Many texture descriptors in texture analysis and image retrieval are based on the so-called Local Binary Pattern (LBP) technique. However, LBP lacks of the spatial distribution information of texture features. In this paper, we aim at improving the traditional LBP and present a novel texture feature descriptor for CBIR called Multi-Scale Local Spatial Binary Patterns (MLSBP). MLSBP integrates LBP with spatial distribution information of gray-level variation direction and gray-level variation between the referenced pixel and its neighbors. In addition, MLSBP extracts the texture features from images on different scale levels. We conduct experiments to compare the performance of MLSBP with five competitors including LBP, Uniform LBP (ULBP), Completed LBP (CLBP), Local Ternary Patterns (LTP), and Local Tetra Patterns (LTrP). Also three benchmark image databases are used in the measurement, which are the Bradotz Texture Database (DB1), the MIT VisTex Database (DB2), and the Corel 1000 Database (DB3). The experimental results show that MLSBP is superior to the competitive algorithms in terms of precision and recall.


Content-based image retrieval Local binary pattern Texture feature Spatial distribution 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys (CSUR) 40(2), 5 (2008)CrossRefGoogle Scholar
  2. 2.
    Liu, G.-H., Zhang, L., Hou, Y.-K., Li, Z.-Y., Yang, J.-Y.: Image retrieval based on multi-texton histogram. Pattern Recognition 43(7), 2380–2389 (2010)CrossRefzbMATHGoogle Scholar
  3. 3.
    Li, W., Duan, L., Xu, D., Tsang, I.W.-H.: Text-based image retrieval using progressive multi-instance learning. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 2049–2055. IEEE (2011)Google Scholar
  4. 4.
    Liu, Y., Zhang, D., Lu, G., Ma, W.-Y.: A survey of content-based image retrieval with high-level semantics. Pattern Recognition 40(1), 262–282 (2007)CrossRefzbMATHGoogle Scholar
  5. 5.
    Ojala, T., Pietikäinen, M., Harwood, D.: A comparative study of texture measures with classification based on featured distributions. Pattern Recognition 29(1), 51–59 (1996)CrossRefGoogle Scholar
  6. 6.
    Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)CrossRefGoogle Scholar
  7. 7.
    Guo, Z., Zhang, L., Zhang, D.: A completed modeling of local binary pattern operator for texture classification. IEEE Transactions on Image Processing 19(6), 1657–1663 (2010)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. In: Zhou, S.K., Zhao, W., Tang, X., Gong, S. (eds.) AMFG 2007. LNCS, vol. 4778, pp. 168–182. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Murala, S., Maheshwari, R.P., Balasubramanian, R.: Local tetra patterns: a new feature descriptor for content-based image retrieval. IEEE Transactions on Image Processing 21(5), 2874–2886 (2012)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Brodatz, P.: Textures: A Photographic Album for Artists and Designers. Dover, New York (1996)Google Scholar
  11. 11.
    Corel 10000 image database,
  12. 12.
    MIT Vision and Modeling Group, Cambridge, Vision texture,

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Yu Xia
    • 1
  • Shouhong Wan
    • 1
  • Peiquan Jin
    • 1
  • Lihua Yue
    • 1
  1. 1.School of Computer Science and TechnologyUniversity of Science and Technology of ChinaChina

Personalised recommendations