Electronic Trace Fossil Image Retrieval Based on Extended Direction Local Binary Pattern

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Advances in Mechanical and Electronic Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 178))

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Abstract

Based on the direction local binary pattern (dLBP) and the center-symmetric local binary pattern (CS-LBP), an improved direction local binary pattern (idLBP) was presented. The directionality, coarseness and contrast of a texture region were considered together in the new definition. LBP, dLBP and idLBP were firstly tested on two commonly used texture image sets. Finally, idLBP was used for electronic trace fossil image retrieval. The results show that idLBP gives the best retrieval performance in the three descriptors.

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References

  1. Ojala, T., Pietikäinen, M., Hardwood, D.: A Comparative Study of Texture Measures with Classification based on Feature Distribution. Pattern Recognition 1, 51–59 (1996)

    Article  Google Scholar 

  2. Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 7, 971–987 (2002)

    Article  Google Scholar 

  3. Zhou, H., Wang, R.S., Wang, C.: A Novel Extended Local-Binary-Pattern Operator for Texture Analysis. Information Sciences 22, 4314–4325 (2008)

    Article  Google Scholar 

  4. Guo, Z., Zhang, L., Zhang, D.: Rotation Invariant Texture Classification using LBP Variance (LBPV) with Global Matching 3, 706–719 (2010)

    Article  Google Scholar 

  5. Tan, X., Triggs, B.: Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions. IEEE Transactions on Image Processing 6, 1635–1650 (2010)

    MathSciNet  Google Scholar 

  6. Sun, J.D., Wu, X.S.: Content-based Image Retrieval based on Texture Spectrum Descriptors. Journal of Computer-Aided Design & Computer Graphics 3, 516–520 (2010) (in Chinese)

    Google Scholar 

  7. Heikkilä, M., Pietikäinen, M., Schmid, C.: Description of Interest Regions with Local Binary Patterns. Pattern Recognition 3, 425–436 (2009)

    Article  Google Scholar 

  8. Trefný, J., Matas, J.: Extended set of local binary patterns for rapid object detection. In: Computer Vision Winter Workshop 2010, Libor Spacek, Vojtech Franc, pp. 1–7 (2010)

    Google Scholar 

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Correspondence to **aosheng Wu .

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Wu, X., Sun, J. (2013). Electronic Trace Fossil Image Retrieval Based on Extended Direction Local Binary Pattern. In: **, D., Lin, S. (eds) Advances in Mechanical and Electronic Engineering. Lecture Notes in Electrical Engineering, vol 178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31528-2_75

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  • DOI: https://doi.org/10.1007/978-3-642-31528-2_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31527-5

  • Online ISBN: 978-3-642-31528-2

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