The KIPS Transactions:PartB (정보처리학회논문지B)

Korea Information Processing Society (한국정보처리학회)
권호 표지
DOI QR코드

DOI QR Code

Comparisons of MPEG-7 Texture Descriptors for Iris recognition

MPEG-7 텍스쳐 서술자의 홍채 인식에 대한 성능 비교

  • 추현곤 (한양대학교 대학원 전자통신전파공학과) ;
  • 김회율 (한양대학교 전자공학과)
  • Published : 2004.08.01
Download PDF
⟨ Previous Next ⟩

Abstract

There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.

MPEG극 텍스쳐 서술자에는 균등 질감(Homogeneous Texture), 경계 히스토그램(Edge Histogram), 텍스쳐 브라우징(Texture Browsing) 서술자가 있다. 본 논문에서는 이들 텍스쳐 서술자를 이용하여 홍채 인식에 대한 성능을 비교 분석한다. 전처리 과정을 통해 추출된 560장의 흥채 영상을 이용하여, 세 서술자에 대한 각 계수에 대한 군집화 효율성 비교와 에러 분포 비교를 통해 서로 다른 홍채 그룹에 대한 변별 능력을 비교한다. 실험 결과를 통해 세 서술자 중 균등 질감 서술자가 홍채 패턴을 인식하는 데 있어서 가장 효율적인 서술자로 나타났다. 그러나, 실험결과는 기존의 홍채 인식 방법에 비해, MPEG-7 텍스쳐 서술자를 이용한 홍채 인식에 인식 성능 향상을 위한 노력이 필요함을 알 수 있다.

Keywords

References

  1. R. Wildes, 'Iris Recognition : An Emerging Biometric Technology,' Proceedings of the IEEE, Vol.85, No.9, pp.1348-1363, Sep., 1997 https://doi.org/10.1109/5.628669
  2. G. Williams, 'Iris Recognition Technology,' IEEE Aerospace and Electronic Systems Magazine, pp.23-29, Apr., 1997 https://doi.org/10.1109/62.575997
  3. B. Manjunath, P. Salembier and T. Sikora, Introduction to MPEG-7, John Wiley & Sons Ltd, 2002
  4. L. Cieplinski, W. Kim, J.-R. Ohm, M. Pickering and A. Yamada, 'MPEG-7 Visual part of eXperimentation Model Version,' ISO/IEC JTC1/SC29/WG11/N4548, Dec., 2001
  5. P. Beek et al., 'Extraction and Use of MPEG-7 Descriptions,' ISO/IEC JTC1/SC29/WG11/N4360, July, 2001
  6. J. Daugman, 'How iris recognition works,' IEEE Transactions on Circuits and Systems for Video Technology, Vol.14, No.1, pp.21-30, Jan., 2004 https://doi.org/10.1109/TCSVT.2003.818350
  7. J. Daugman, 'High Confidence Visual Recognition of Persons by a Test of Statistical Independence,' IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.15, pp.1148-1161, 1993 https://doi.org/10.1109/34.244676
  8. J. Daugman, 'The importance of being random : Statistical principles of iris recognition,' Pattern Recognition, Vol.36, No.2, pp.279-291, Feb., 2003 https://doi.org/10.1016/S0031-3203(02)00030-4
  9. Yong Man Ro, Munchurl Kim, Ho Kyung Kang, B. Manjunath and Jinwoong Kim, 'MPEG-7 Homogeneous Texture Descriptor,' ETRI Journal, Vol.23, No.2, pp.41-51, June, 2001 https://doi.org/10.4218/etrij.01.0101.0201
  10. Yong Man Ro and Ho Kyung Kang, 'Hierarchical rotational invariant similarity measurement for MPEG-7 homogeneous texture descriptor,' Electronics Letters, Vol.36, No.15, pp.1268-1270, July, 2000 https://doi.org/10.1049/el:20000949
  11. B. Manjunath, J. Ohm, V. Vasudevan and A. Yamada, 'Color and texture descriptors,' IEEE Transactions on Circuits and Systems for Video Technology, Vol.11, No.6, pp.703-715, June, 2001 https://doi.org/10.1109/76.927424

Cited by

  1. Iris Recognition Using Vector Summation Of Gradient Orientation Vectors vol.9, pp.8, 2009, https://doi.org/10.5392/JKCA.2009.9.8.121
  2. Effective Water Pollution Management using Reservoir Tank Automatic Classification vol.9, pp.8, 2009, https://doi.org/10.5392/JKCA.2009.9.8.001