Skip to main content

Advertisement

SpringerLink
Log in

Face description based on adaptive local weighted Gabor comprehensive histogram feature

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Face recognition is an extensively research topic in pattern recognition and image processing fields due to its broad application prospects in many areas such as counter terrorism, access identification, electronic passport, e-government affairs, etc. Inspired by the Gabor phase information and local image information content, a novel face description algorithm using adaptive Local Weighted Gabor Comprehensive Histogram (LWGCH) is proposed. It consists of two components: Local Gabor Comprehensive Histogram (LGCH) and Contribution Map (CM). Actually, the adaptive local weighted Gabor comprehensive histogram is generated with LGCH weighed by CM calculated by information content model. Finally, Extensive experiments on ORL, YALE, CMUPIE and Yale B face databases validate the effectiveness of the proposed methods under various conditions of partial occlusion, complex illumination, different expressions and poses. Experimental results indicate that the proposed algorithm is a competitive and robust method compared with several state-of-the-art approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Conde C, Moctezuma D, De Diego IM et al (2013) HoGG: gabor and HoG-based human detection for surveillance in non-controlled environments[J]. Neurocomputing 100:19–30

    Article  Google Scholar 

  2. Cui Y, Fan LY (2012) A novel supervised dimensionality reduction algorithm: graph based Fisher analysis [J]. Pattern Recogn 45(2):1471–1481

    Article  MATH  Google Scholar 

  3. Daugman JG (1985) Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters[J]. JOSA A 2(7):1160–1169

    Article  Google Scholar 

  4. Fabregas J, Faundez-Zanuy M (2008) Biometric dispersion matcher versus LDA [J]. Pattern Recogn 41(11):3412–3426

    Article  MATH  Google Scholar 

  5. Fernandes SL, Bala GJ (2013) A comparative study on ICA and LPP based face recognition under varying illuminations and facial expressions[C]. Int Conf Signal Proc Image Proc Patt Recog (ICSIPR) 2013:122–126

    Google Scholar 

  6. Găianu M, Onchiş DM (2014) Face and marker detection using gabor frames on GPUs[J]. Signal Process 96:90–93

    Article  Google Scholar 

  7. Gao T, He M (2008) A novel face description by local multi-channel Gabor histogram sequence binary pattern[C]//audio, language and image processing, 2008. ICALIP. IEEE Int Conf on 2008:1240–1244

    Google Scholar 

  8. Gupta S, Jaafar J, Ahmad WFW (2012) Static hand gesture recognition using local gabor filter[J]. Procedia Eng 41:827–832

    Article  Google Scholar 

  9. Hsieh P-C, Tung P-C (2009) A novel hybrid approach based on sub-pattern technique and whitened PCA for face recognition [J]. Pattern Recogn 42(1):978–984

    Article  MATH  Google Scholar 

  10. Kanan HR, Faez K (2010) Recognizing faces using adaptively weighted Sub-gabor array from a single sample image per enrolled subject[J]. Image Vis Comput 28(3):438–448

    Article  Google Scholar 

  11. Kirby M, Sirovich L (1990) Application of the KL procedure for the characterization of human faces. [J]. IEEE Trans Pattern Anal Mach Intell 12(1):103–108

    Article  Google Scholar 

  12. Li S, Lu H-C, Ruan X, Chen Y-W (2012) Human body segmentation based on independent component analysis with reference at two-scale super pixel [J]. Image Proc IET 6(6):770–777

    Article  Google Scholar 

  13. Liu H (2012) Force field convergence map and Log-gabor filter based multi-view ear feature extraction[J]. Neurocomputing 76(1):2–8

    Article  Google Scholar 

  14. Mak KL, Peng P, Yiu KFC et al (2013) Multi-dimensional complex-valued gabor wavelet networks[J]. Math Comput Model 58(11):1755–1768

    Article  MathSciNet  MATH  Google Scholar 

  15. Masutani Y, MacMahon H, Doi K (2001) Automated segmentation and visualization of the pulmonary vascuar tree in spiral CT angiography: an anatomy-oriend approach based on three-dimensional image analysis [J]. J Comput Assist Tomogr 24(4):587–597

    Article  Google Scholar 

  16. Meng J, Zhang W (2007) Volume measure in 2DPCA-based face recognition [J]. Pattern Recogn Lett 28(10):1203–1208

    Article  Google Scholar 

  17. Newman DJ, Block S (2006) Probabilistic topic decomposition of an eighteenth century newspaper [J]. J Am Soc Inf Sci Technol 57(6):753–767

    Article  Google Scholar 

  18. Oh JH, Kwak N (2013) Generalization of linear discriminant analysis using Lp-norm [J]. Pattern Recogn Lett 34(6):679–685

    Article  Google Scholar 

  19. Ojala T, Pietikainen M, Maenpaa T (2002) Multire solution gray-scale and rotation invariant texture classification with local binary patterns [J]. IEEE Trans Pattern Anal Mach Intell 24(7):971–987

    Article  Google Scholar 

  20. Ojala T, Pietikainen M, MaenpaaT (2001) A generalized local binary pattern operator for multi resolution grey scale and rotation invariant texture classification [M].Lecture Notes in Computer Science. Heidelberg: Springer, 2013: 397–406

  21. Pong KH, Lam KM (2014) Multi-resolution feature fusion for face recognition[J]. Pattern Recogn 47(2):556–567

    Article  Google Scholar 

  22. Selvan S, Borckmans P, Chattopadhyay A, Absil P (2013) Spherical mesh adaptive direct search for separating quasi-uncorrelated sources by range-based independent component analysis [J]. Neural Comput 25(9):2486–2522

    Article  MathSciNet  Google Scholar 

  23. Sharma A, Paliwal KK (2008) Cancer classification by gradient LDA technique using microarray gene expression data [J]. Data Knowl Eng 66(2):338–347

    Article  Google Scholar 

  24. Sharma A, Paliwal KK, Onwubolu GC (2006) Class-dependent PCA, MDC and LDA: a combined classifier for pattern classification [J]. Pattern Recogn 39(7):1215–1229

    Article  MATH  Google Scholar 

  25. Shin K, Feraday SA, Harris CJ, Brennan MJ (2003) Optimal auto-regressive modelling of a measured noisy deterministic signal using singular-value decomposition [J]. Mech Syst Signal Process 17(2):423–432

    Article  Google Scholar 

  26. Shu X, Gao Y, Hongtao L (2012) Efficient linear discriminant analysis with locality preserving for face recognition [J]. Pattern Recogn 45(5):1892–1898

    Article  MATH  Google Scholar 

  27. Strecha C, Bronstein A, Bronstein M, Fua P (2012) LDAHash: improved matching with smaller descriptors [J]. IEEE Trans Pattern Anal Mach Intell 34(1):66–78

    Article  Google Scholar 

  28. Su Y, Shan S, Chen X et al (2009) Hierarchical ensemble of global and local classifiers for face recognition[J]. Image Proc IEEE Trans 18(8):1885–1896

    Article  MathSciNet  Google Scholar 

  29. Sun Z, Lam K-M (2011) Depth estimation of face images based on the constrained ICA model [J]. IEEE Trans Inf Forensics Secur 6(2):360–370

    Article  Google Scholar 

  30. Tan K, Chen S (2005) Adaptively weighted sub-pattern PCA for face recognition [J]. Neurocomputing 64(1):505–511

    Article  MathSciNet  Google Scholar 

  31. Tan X, Triggs B (2010) Enhanced local texture feature sets for face recognition under difficult lighting conditions[J]. Image Proc IEEE Trans 19(6):1635–1650

    Article  MathSciNet  Google Scholar 

  32. Toutanova K, Johnson M (2007) A Bayesian LDA-based model for semi-supervised part of speech tagging [C]. Proc Neural Inf Proc Syst (NIPS2007) Vancouver, BC, Canada 20:1521–1528

    Google Scholar 

  33. Walton J, Fairley N (2005) Noise reduction in X-ray photoelectron spectromicroscopy by a singular value decomposition sorting procedure [J]. J Electron Spectrosc Relat Phenom 148(1):29–40

    Article  Google Scholar 

  34. Wei JJ, Chang CJ, Chou N (2001) K.ECG data compression using truncated singular value decomposition [J]. IEEE Trans Inf Technol Biomed 5(4):290–299

    Article  Google Scholar 

  35. Wong WK, Zhao HT (2012) Supervised optimal locality preserving projection [J]. Pattern Recogn 45(1):186–197

    Article  MATH  Google Scholar 

  36. Wu M, Zhou J, Sun J (2012) Multi-scale ICA texture pattern for gender recognition [J]. Electron Lett 48(11):629–631

    Article  Google Scholar 

  37. Xie S, Shan S, Chen X et al (2010) Fusing local patterns of gabor magnitude and phase for face recognition[J]. Image Proc IEEE Trans 19(5):1349–1361

    Article  MathSciNet  Google Scholar 

  38. Yang J, Liu C (2007) Horizontal and vertical 2DPCA-based discriminant analysis for face verification on a large-scale database [J]. IEEE Trans Inf Forensics Secur 2(4):781–792

    Article  MathSciNet  Google Scholar 

  39. Yang W, Sun C, Zhang L (2011) A multi-manifold discriminant analysis method for image feature extraction [J]. Pattern Recogn 44(8):1649–1657

    Article  MATH  Google Scholar 

  40. Yang M, Zhang L, Shiu SCK et al (2013) Gabor feature based robust representation and classification for face recognition with Gabor occlusion dictionary[J]. Pattern Recogn 46(7):1865–1878

    Article  Google Scholar 

  41. 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]. Image Proc IEEE Trans 19(2):533–544

    Article  MathSciNet  Google Scholar 

  42. Zhang B, Shan S, Chen X et al (2007) Histogram of Gabor phase patterns (HGPP): a novel object representation approach for face recognition[J]. Image Proc IEEE Trans 16(1):57–68

    Article  MathSciNet  Google Scholar 

  43. Zhang W, Shan S, Gao W et al (2005) Local gabor binary pattern histogram sequence (lgbphs): a novel non-statistical model for face representation and recognition[C]//Computer vision, 2005. ICCV 2005. Tenth IEEE Int Conf IEEE 1:786–791

    Google Scholar 

  44. Zhang W, Shan S, Qing L et al (2009) Are gabor phases really useless for face recognition?[J]. Pattern Anal Applic 12(3):301–307

    Article  MathSciNet  Google Scholar 

  45. Zhao CR, Miao DQ, Lai ZH, Gao C, Liu CC, Yang JY (2013) Two-dimensional color uncorrelated discriminant analysis for face recognition [J]. Neurocomputing 113(3):251–261

    Article  Google Scholar 

  46. Zhao ZS, Zhang L, Zhao M et al (2012) Gabor face recognition by multi-channel classifier fusion of supervised kernel manifold learning[J]. Neurocomputing 97:398–404

    Article  Google Scholar 

  47. Zhou SR, Yin JP, Zhang JM (2013) Local binary pattern (LBP) and local phase quantization (LBQ) based on Gabor filter for face representation[J]. Neurocomputing 116:260–264

    Article  Google Scholar 

  48. Zuñiga AG, Florindo JB, Bruno OM (2014) Gabor wavelets combined with volumetric fractal dimension applied to texture analysis[J]. Pattern Recogn Lett 36:135–143

    Article  Google Scholar 

Download references

Acknowledgment

This project is supported by the National Natural Science Foundation of China (61302150), Natural Science Foundation of Shanxi Province, China (2013JQ8044), China Postdoctoral Science Foundation (2014 M562356), Xi’an Science and technology development project(CXY1341(8)).

Author information

Authors and Affiliations

  1. School of Information Engineering, Chang’an University, Xi’An, 710064, China

    Tao Gao, X. M. Zhao, Ting Chen, Z. W. Liu & Ce Ni

Authors
  1. Tao Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. X. M. Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ting Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Z. W. Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ce Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tao Gao.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, T., Zhao, X.M., Chen, T. et al. Face description based on adaptive local weighted Gabor comprehensive histogram feature. Multimed Tools Appl 76, 12893–12916 (2017). https://doi.org/10.1007/s11042-016-3701-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3701-y

Keywords

Search

Navigation