Skip to main content
SpringerLink
Log in

Fused Local Color Pattern (FLCP): A Novel Color Descriptor for Face Recognition

  • Conference paper
  • First Online:
Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022) (SoCPaR 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 648))

Included in the following conference series:

Abstract

Literature suggests that when color information is used then there is immense improvement in accuracy. This work presented such novel descriptor so-called Fused Local Color Pattern (FLCP) by using the RGB color format. Precisely from R component MRELBP-NI is imposed for feature extraction, from G component 6 × 6 MB-LBP is imposed for feature extraction and from B component RD-LBP is imposed for feature extraction. The features extracted from all three components are joined which is called as FLCP. Compaction and matching is done by PCA and SVMs. Results on GT confirms the effectiveness of the FLCP descriptor as compared to the individually implemented gray scale based descriptors. FLCP also outperforms various literature methods. The novelty of proposed work is the development of discriminant descriptor by fusing the features extracted from RGB color format. This concept is lacking in the previous work.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Karanwal, S., Diwakar, M.: Two novel color local descriptors for face recognition. Opt 226 (2021)

    Google Scholar 

  2. Zhu, C., Bichot, C.E., Chen, L.: Image region description using OC-LBP enhanced with color information. Patt. Recog. 46(7), 1949–1963 (2013)

    Article  Google Scholar 

  3. Karanwal, S.: DCD by fusion of three novel color descriptors. Opt 244 (2021)

    Google Scholar 

  4. Agarwal, M., Singhal, A., Lall, B.: Multi-channel LTP for CBIR. Pat. Ana. App. 22, 1585–1596 (2019)

    Article  Google Scholar 

  5. Liu, L., Lao, S., Fieguth, P.W., Guo, Y., Wang, X., Pietikainen, M.: MRELBP for texture classification. IEEE Tran. Img. Proc. 25(3), 1368–1381 (2016)

    Article  MATH  Google Scholar 

  6. Liao, S., Zhu, X., Lei, Z., Zhang, L., Li, S.Z.: Learning MB-LBP for FR. In: ICB, pp. 828–837 (2007)

    Google Scholar 

  7. Liu, L., Zhao, L., Long, Y., Kuang, G., Fieguth, P.: Extended LBP for texture. Img. Vis. Com. 30(2), 86–99 (2012)

    Article  Google Scholar 

  8. Kravchik, M., Shabtai, A.: ECAD in ICS using lightweight NNs and PCA. IEEE Tran Dep Sec Com (2021)

    Google Scholar 

  9. Hazarika, B.B., Gupta, D.: DW-SVMs for binary class imbalance learning. Neu. Com. App. 33, 4243–4261 (2021)

    Article  Google Scholar 

  10. http://www.anefian.com/research/face_reco.htm

  11. Chaudhari, V., Dawoodi, H.H., Patil, M.P.: BLDR based on LBP. In: STCC, pp. 653–661 (2021)

    Google Scholar 

  12. Karanwal, S.: Improved LBP for FR. In: ICDLAIR, pp. 86–96 (2022)

    Google Scholar 

  13. Khanna, K., Gambhir, S., Gambhir, M.: A novel technique for image classification using STFT and LBP. Multm. Tool Appl. 81, 20705–20718 (2022)

    Article  Google Scholar 

  14. Vu, H.N., Nguyen, M.H., Pham, C.: Masked FR with CNN and LBP. Appl. Intell. 52, 5497–5512 (2022)

    Article  Google Scholar 

  15. Wang, J.: Fusing GGF and LBP for texture image recognition. In: ICIVIS, pp. 309–319 (2021)

    Google Scholar 

  16. Karanwal, S., Diwakar, M.: BILBD for face recognition. J. Inf. Assoc. Sec. 17(1) (2022)

    Google Scholar 

  17. Karanwal, S., Diwakar, M.: MB-ZZLBP for face recognition. In: MARC, pp. 613–622 (2021)

    Google Scholar 

  18. Borlea, I.D., Precup, R.E., Borlea, A.B.: Improvement of K-means cluster quality by PPRC. Pro. Com. Sci. 199, 63–70 (2022)

    Google Scholar 

  19. Zhang, Y., Liu, W., Fan, H., Zou, Y., Cui, Z., Wang, Q.: Dictionary learning and face recognition based on sample expansion. App. Int. 52, 3766–3780 (2021)

    Google Scholar 

  20. Karanwal, S., Roka, S.: RFD under unconstrained conditions. In: SUSCOM (2022)

    Google Scholar 

  21. Ran, R., Feng, J., Zhang, S., Fang, B.: A GMFDR framework and extension for ML. IEEE Tran. Cyb. 52(4), 2137–2148 (2022)

    Article  Google Scholar 

  22. Karanwal, S.: Robust LBP for face recognition in different challenges. Multim. Tool Appl. 81, 29405–29421 (2022)

    Google Scholar 

  23. Karanwal, S.: GBSBP for face analysis. Opt 241 (2021)

    Google Scholar 

  24. Zeng, S., Gou, J., Deng, L.: An antinoise SR method for RFR via joint l1 and l2 regularization. Exp. Syst. Appl. 82, 1–9 (2017)

    Article  Google Scholar 

  25. Zhang, K., Peng, Y., Liu, S.: Discriminative FR via KSR. Multim. Tool Appl. 77, 32243–32256 (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of CSE, Graphic Era University, Dehradun, UK, India

    Shekhar Karanwal

Authors
  1. Shekhar Karanwal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shekhar Karanwal .

Editor information

Editors and Affiliations

  1. Faculty of Computing and Data Science, FLAME University, Pune, Maharashtra, India

    Ajith Abraham

  2. University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland

    Thomas Hanne

  3. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, AL, USA

    Niketa Gandhi

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Mala, Kerala, India

    Pooja Manghirmalani Mishra

  5. Computer Science and Engineering Department, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Anu Bajaj

  6. Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Karanwal, S. (2023). Fused Local Color Pattern (FLCP): A Novel Color Descriptor for Face Recognition. In: Abraham, A., Hanne, T., Gandhi, N., Manghirmalani Mishra, P., Bajaj, A., Siarry, P. (eds) Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022). SoCPaR 2022. Lecture Notes in Networks and Systems, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-031-27524-1_8

Download citation

Publish with us

Policies and ethics

Search

Navigation