Chain Code Histogram Based Facial Image Feature Extraction under Degraded Conditions

  • Soyuj Kumar Sahoo
  • Jitendra Jain
  • S. R. Mahadeva Prasanna
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 192)


In this work, we have introduced a feature extraction method based on Chain Code Histogram (CCH) for facial images. A face verification (FV) system has been developed by using CCH feature. The performance of the above system is comparable with that of subspace analysis methods, i.e. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) under degraded condition. All the experimental results are shown upon a subset of IITG MV multi-biometric database which is a real time degraded office environment database. Finally, a better improved verification performance is reported by using the combination of both features which strongly validates the different information representation of both methods.


Chain Code Histogram Face Verification Degraded Environment Feature combination PCA-LDA 


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  1. 1.
    Kimura, F., Wakabayashi, T., Tsuruoka, S., Miyake, Y.: Improvement of handwritten Japanese character recognition using weighted direction code histogram. Pattern Recognition 30(3), 1329–1337 (1997)CrossRefGoogle Scholar
  2. 2.
    Pal, U., Sharma, N., Wakabayashi, T., Kimura, F.: Off-Line Handwritten Character Recognition of Devnagari Script. In: Proc. 9th Int. Conf. Document Analysis and Recognition (ICDAR), vol. 1, pp. 496–500 (2007)Google Scholar
  3. 3.
    Arora, S., Bhattacharjee, D., Nasipuri, M., Basu, D.K., Kundu, M.: Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition. In: Proc. IEEE Region 10 and the 3rd Int. Conf. Industrial and Information Systems (ICIIS), pp. 1–6 (2008)Google Scholar
  4. 4.
    Roy, K., Pal, T., Pal, U., Kimura, F.: Oriya Handwritten Numeral Recognition System. In: Proc. 8th Int. Conf. Document Analysis and Recognition (ICDAR), vol. 2, pp. 770–774 (2005)Google Scholar
  5. 5.
    Lawal, I.A., Abdel-Aal, R.E., Mahmoud, S.A.: Recognition of Handwritten Arabic (Indian) Numerals Using Freeman’s Chain Codes and Abductive Network Classifiers. In: Proc. 20th Int. Conf. Pattern Recognition (ICPR), pp. 1884–1887 (2010)Google Scholar
  6. 6.
    Chen, L., Liao, H., Ko, M., Lin, J., Yu, G.: A new LDA-based face recognition system which can solve the small sample size problem. Pattern Recognition 33(10), 1713–1726 (2000)CrossRefGoogle Scholar
  7. 7.
    Martinez, A., Kak, A.: PCA versus LDA. IEEE Trans. Pattern Analysis and Machine Intelligence 23(2), 228–233 (2001)CrossRefGoogle Scholar
  8. 8.
    Sahoo, S.K., Prasanna, S.R.M.: Bimodal Biometric Person Authentication using Speech and Face under Degraded Condition. In: Proc. National Conference on Communication, NCC (2011)Google Scholar
  9. 9.
    Canny, J.: A Computational Approach To Edge Detection. IEEE Trans. Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)CrossRefGoogle Scholar
  10. 10.
    Linde, Y., Buzo, A., Gray, R.M.: An algorithm for vector quantizer design. IEEE Trans. On Communications COM-28, 84–95 (1980)CrossRefGoogle Scholar
  11. 11.
    Martin, A., Doddington, G., Kamm, T., Ordowski, M., Przybocki, M.: The det curve in asssessment of detection task performance. In: Proc. Eur. Conf. Speech Communication Technology, pp. 1895–1898 (1997)Google Scholar
  12. 12.
    Bimbot, F., Bonastre, J.F., Fredouille, C., Gravier, G., Chagnolleau, M.I., Meignier, S., Merlin, T., García, O.J., Delacrétaz, P.D., Reynolds, D.A.: A tutorial on text-independent speaker verification. EURASIP J. Appl. Signal Process. 4, 430–451 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Soyuj Kumar Sahoo
    • 1
  • Jitendra Jain
    • 1
  • S. R. Mahadeva Prasanna
    • 1
  1. 1.Electro Medical & Speech Technology LabIndian Institute of Technology GuwahatiGuwahatiIndia

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