A novel local texture feature extraction method called multi-direction local binary pattern

  • Jin LiuEmail author
  • Yue Chen
  • Shengnan Sun


A novel method named MD-LBP (Multi-Direction Local Binary Pattern) is proposed in this paper to capture the excellent local texture features. Based on LBP (Local Binary Pattern), the proposed method is a local feature extraction method, which optimized the coding scheme by considering the relationship between the center pixel and the weighted pixels in its neighborhood. Furthermore, unlike the original gray scale histogram method, the proposed method used a new way to get the feature vector which not only describes the holistic spatial information of image, but also reduces the image dimension. The proposed method is evaluated by extensive experiments on benchmark databases, such as CMU PIE and Extended Yale B face database, PolyU and CASIA Palmprint database. The experimental results show that the proposed method MD-LBP, can significantly capture the useful local texture features, and improve the recognition rates both in face and palmprint fields.


Face recognition Palmprint recognition Local feature extraction Multi-direction local binary pattern 



We would like to thank the associate editor and all anonymous reviewers for their constructive comments and suggestions. And portions of the research in this paper use the CASIA Palmprint Database collected by the Chinese Academy of Sciences’ Institute of Automation (CASIA). This research was partially supported by the National Science Foundation of China (Grant No. 61101246) and the Fundamental Research Funds for the Central Universities (Grant No. JB150209).


  1. 1.
    Ahmed F, Kabir MH (2012) Directional ternary pattern (dtp) for facial expression recognition[C]. In: Consumer electronics (ICCE), 2012 IEEE international conference on. IEEE, pp 265–266Google Scholar
  2. 2.
    Alsubari A, Ramteke RJ (2017) Extraction of face and Palmprint features based on LBP, HOG and Zernike moments[J]. Extraction 172(5)Google Scholar
  3. 3.
    CASIA palmprint database (2018) Accessed 22 May 2018
  4. 4.
    Chakraborty S, Singh SK, Chakraborty P (2017) Local directional gradient pattern: a local descriptor for face recognition[J]. Multimed Tools Appl 76(1):1201–1216CrossRefGoogle Scholar
  5. 5.
    Chen C, Zhang B, Su H et al (2016) Land-use scene classification using multi-scale completed local binary patterns[J]. SIViP 10(4):745–752CrossRefGoogle Scholar
  6. 6.
    Chen Z, Zhu Q, Soh YC et al (2017) Robust human activity recognition using smartphone sensors via CT-PCA and online SVM[J]. IEEE Transactions on Industrial Informatics 13(6):3070–3080CrossRefGoogle Scholar
  7. 7.
    CMUPIE dataset (2016) Accessed 15 Nov 2018
  8. 8.
    Ding M, Fan G (2015) Multilayer joint gait-pose manifolds for human gait motion modeling[J]. IEEE Transactions on Cybernetics 45(11):2413–2424CrossRefGoogle Scholar
  9. 9.
    Ding C, Choi J, Tao D et al (2016) Multi-directional multi-level dual-cross patterns for robust face recognition[J]. IEEE Trans Pattern Anal Mach Intell 38(3):518–531CrossRefGoogle Scholar
  10. 10.
    Fei L, Xu Y, Teng S et al (2017) Local orientation binary pattern with use for Palmprint recognition[C]. In: Chinese conference on biometric recognition. Springer, Cham, pp 213–220Google Scholar
  11. 11.
    Fronitasari D, Gunawan D (2017) Palm vein recognition by using modified of local binary pattern (LBP) for extraction feature [C]. In: Quality in research (QiR): international symposium on electrical and computer engineering, 2017 15th international conference on. IEEE, pp 18–22Google Scholar
  12. 12.
    Guo Z, Zhang L, Zhang D (2010) A completed modeling of local binary pattern operator for texture classification[J]. IEEE Trans Image Process 19(6):1657–1663MathSciNetCrossRefGoogle Scholar
  13. 13.
    Han D, Guo Z, Zhang D (2008) Multispectral palmprint recognition using wavelet-based image fusion[C]. In: Signal processing, 2008. ICSP 2008. 9th international conference on. IEEE, pp 2074–2077Google Scholar
  14. 14.
    Heikkilä M, Pietikäinen M, Schmid C (2009) Description of interest regions with local binary patterns[J]. Pattern Recogn 42(3):425–436CrossRefGoogle Scholar
  15. 15.
    Jabid T, Kabir MH, Chae O (2010) Local directional pattern (LDP) for face recognition[C]. In: Consumer electronics (ICCE), 2010 digest of technical papers international conference on. IEEE, pp 329–330Google Scholar
  16. 16.
    Leng L, Zhang J, Khan MK et al (2010) Dynamic weighted discrimination power analysis: a novel approach for face and palmprint recognition in DCT domain[J]. International Journal of Physical Sciences 5(17):2543–2554Google Scholar
  17. 17.
    Leng L, Zhang J, Chen G et al (2011) Two-directional two-dimensional random projection and its variations for face and palmprint recognition[C]. In: International conference on computational science and its applications. Springer, Berlin, pp 458–470Google Scholar
  18. 18.
    Leng L, Li M, Kim C et al (2017) Dual-source discrimination power analysis for multi-instance contactless palmprint recognition[J]. Multimed Tools Appl 76(1):333–354CrossRefGoogle Scholar
  19. 19.
    Liu Y, Nie L, Han L et al (2015) Action2Activity: recognizing complex activities from sensor data[C]. In: IJCAI, 2015, pp 1617–1623Google Scholar
  20. 20.
    Lu W, Li M, Zhang L (2016) Palm vein recognition using directional features derived from local binary patterns[J]. Structure 9(5)Google Scholar
  21. 21.
    Luo YT, Zhao LY, Zhang B et al (2016) Local line directional pattern for palmprint recognition[J]. Pattern Recogn 50:26–44CrossRefGoogle Scholar
  22. 22.
    Mirmohamadsadeghi L, Drygajlo A (2011) Palm vein recognition with local binary patterns and local derivative patterns [C]. In: Biometrics (IJCB), 2011 international joint conference on. IEEE, pp 1–6Google Scholar
  23. 23.
    Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[J]. IEEE Trans Pattern Anal Mach Intell 24(7):971–987CrossRefGoogle Scholar
  24. 24.
    Petpon A, Srisuk S (2009) Face recognition with local line binary pattern[C]. In: Image and graphics, 2009. ICIG'09. fifth international conference on. IEEE, pp 533–539Google Scholar
  25. 25.
    PolyU multispectral palmprint database (2018) Accessed 23 May 2018
  26. 26.
    Ramteke RJ, Alsubari A (2016) Extraction of palmprint texture features using combined DWT-DCT and local binary pattern[C]. In: Next generation computing technologies (NGCT), 2016 2nd international conference on. IEEE, pp 748–753Google Scholar
  27. 27.
    Rivera AR, Castillo JR, Chae OO (2013) Local directional number pattern for face analysis: face and expression recognition[J]. IEEE Trans Image Process 22(5):1740–1752MathSciNetCrossRefGoogle Scholar
  28. 28.
    Tan X, Triggs B (2010) Enhanced local texture feature sets for face recognition under difficult lighting conditions[J]. IEEE Trans Image Process 19(6):1635–1650MathSciNetCrossRefGoogle Scholar
  29. 29.
    Wagstaff K, Cardie C, Rogers S et al (2001) Constrained k-means clustering with background knowledge[C]. In: ICML, vol 1, pp 577–584Google Scholar
  30. 30.
    Wen Y, Zhang K, Li Z et al (2016) A discriminative feature learning approach for deep face recognition[C]. In: European conference on computer vision. Springer, Cham, pp 499–515Google Scholar
  31. 31.
    Yale B dataset (2016) Accessed 6 Dec 2016
  32. 32.
    Yang B, Chen S (2013) A comparative study on local binary pattern (LBP) based face recognition: LBP histogram versus LBP image[J]. Neurocomputing 120:365–379CrossRefGoogle Scholar
  33. 33.
    Yang W, Wang Z, Zhang B (2016) Face recognition using adaptive local ternary patterns method[J]. Neurocomputing 213:183–190CrossRefGoogle Scholar
  34. 34.
    Zhang G, Huang X, Li SZ et al (2004) Boosting local binary pattern (LBP)-based face recognition[M]. Advances in biometric person authentication. Springer, Berlin, pp 179–186CrossRefGoogle Scholar
  35. 35.
    Zhang L, Chu R, Xiang S et al (2007) Face detection based on multi-block lbp representation[C]. In: International conference on biometrics. Springer, Berlin, pp 11–18Google Scholar
  36. 36.
    Zhang B, Gao Y, Zhao S et al (2010) Local derivative pattern versus local binary pattern: face recognition with high-order local pattern descriptor[J]. IEEE Trans Image Process 19(2):533–544MathSciNetCrossRefGoogle Scholar
  37. 37.
    Zhang D, Guo Z, Lu G et al (2010) An online system of multispectral palmprint verification[J]. IEEE Trans Instrum Meas 59(2):480–490CrossRefGoogle Scholar
  38. 38.
    Zhao Y, Jia W, Hu RX et al (2013) Completed robust local binary pattern for texture classification[J]. Neurocomputing 106:68–76CrossRefGoogle Scholar
  39. 39.
    Zhou D, Yang D, Zhang X (2017) Exploring joint encoding of multi-direction local binary patterns for image classification [J]. Multimed Tools Appl:1–25Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Electronic EngineeringXidian UniversityXi’anChina

Personalised recommendations