International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 5, No. 11, 8 Nov. 2013
Cover page and Table of Contents: PDF (size: 161KB)
A Biometric Based: 3-D Ear Recognition System Combining Local and Holistic Features
Full Text (PDF, 161KB), PP.36-41
Views: 0 Downloads: 0
Author(s)
Index Terms
Biometrics, Ear biometrics, 3D ear recognition, 3D keypoint detection, shape index, voxelization.
Abstract
This paper introduces an improved ear recognition approach based on 3 dimensional keypoint matching and combining local and holistic features. At first, the 3D keypoints are detected using the shape index image. The system consists of four primary steps: i) ear image segmentation; ii) local feature extraction and matching; iii) holistic feature extraction and matching; and iv) combination of local and holistic features at the match score level. For the segmentation purpose, we use an efficient skin segmentation algorithm, to localize a rectangular region containing the ear. For the local feature extraction and representation purpose, we use the Sparse Representation based Localized Feature Extraction. For the holistic matching component, we introduce a voxelization scheme for holistic ear representation. The match scores obtained from both the local and holistic matching components are combined to generate the final match scores.
Cite This Paper
Akkas Ali, Mohammad. Mahfuzul Islam, "A Biometric Based: 3-D Ear Recognition System Combining Local and Holistic Features", International Journal of Modern Education and Computer Science (IJMECS), vol.5, no.11, pp.36-41, 2013. DOI:10.5815/ijmecs.2013.11.05
Reference
[1]Kyong Chang and Kevin W. Bowyer, Sudeep Sarkar and Barnabas Victor, “Comparison and Combination of Ear and Face Images in Appearance-Based Biometrics”, IEEE Transactions on Pattern Analysis And Machine Intelligence, September 2003, 25(9), pp. 1160-1165.
[2]Hui Chen and Bir Bhanu. “Efficient Recognition of Highly Similar 3D Objects in Range Images”, IEEE Transactions on Pattern Analysis And Machine Intelligence, January 2009, 31(1), pp. 172-179.
[3]K. Chang, K. Bowyer, and V. Barnabas. Comparison and combination of ear and face images in appearance based biometrics. IEEE Transaction on Pattern Analysis and Machine Intelligence, 25:1160–1165, 2003.
[4]M. Kass, A.Witkin, and D. Terzopoulos. Snakes: Active contour models. International Journal of Computer Vision, 1(4):321–331, 1987.
[5]H. Chen and B. Bhanu. Contour matching for 3D ear recognition. Seventh IEEE Workshop on Application of Computer Vision, pages 123–128, 2005.
[6]B. Bhanu and H. Chen. Human ear recognition in 3D. Workshop on Multimodal User Authentication, pages 91–98, 2003.
[7]H. Chen and B. Bhanu. Contour matching for 3D ear recognition. Seventh IEEE Workshop on Application of Computer Vision, pages 123–128, 2005.
[8]H. Chen and B. Bhanu. Human ear detection from side face range images. International Conference on Pattern Recognition, pages 574–577, 2004.
[9]D. Hurley, M. Nixon, and J. Carter. Force field energy functionals for image feature extraction. Image and Vision Computing Journal, 20:429–432, 2002.
[10]D. Hurley, M. Nixon, and J. Carter. Force field energy functionals for ear biometrics. Computer Vision and Image Understanding, 98(3):491–512, 2005.
[11]B. Victor, K. Bowyer, and S. Sarkar. An evaluation of face and ear biometrics. 16th International Conference of Pattern Recognition, pages 429–432, 2002.
[12]K. Chang, K. Bowyer, and V. Barnabas. Comparison and combination of ear and face images in appearance based biometrics. IEEE Transaction on Pattern Analysis and Machine Intelligence, 25:1160–1165, 2003.
[13]B. Moreno, A. Sanchez, and J. Velez. On the use of outer ear images for personal identification in security applications. IEEE International Carnaham Conference on Security Technology, pages 469–476, 1999.
[14]T. Yuizono, Y. Wang, K. Satoh, and S. Nakayama. Study on individual recognition for ear images by using genetic local search. Proceedings of the 2002 Congress on Evolutionary Computation, pages 237–242, 2002.
[15]K. Pun and Y. Moon. Recent advances in ear biometrics. Proceedings of the Sixth International Conference on Automatic Face and Gesture Recognition, pages 164–169, May, 2004.
[16]P. Yan and K.W. Bowyer. Ear biometrics using 2D and 3D images, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05) - Workshops, page 121, 2005.
[17]P. Yan and K. W. Bowyer. Empirical evaluation of advanced ear biometrics, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05) - Workshops, page 41, 2005.
[18]C. Dorai and A. Jain, COSMOS – A Representation Scheme for 3D Free-Form Objects, IEEE Transactions on Pattern Analysis And Machine Intelligence, October 1997, 19(10), pp. 1115-1130.
[19]Surya Prakash, Umarani Jayaraman and Phalguni Gupta (2009) Proceedings of International Conference on Advances in Pattern Recognition, ICAPR' 09, Kolkata, India, 213-216.
[20]A. Beck and M. Teboulle, “A fast iterative shrinkage thresholding algorithm for linear inverse problem,” SIAM Journal on Imaging Sciences, vol. 2, pp. 183–202, 2009.
[21]S.Wang and A. Kaufman, “Volume sampled voxelization of geometric primitives,” in Proc. 4th Conf. Visualization, 1993, pp. 78–84.
[22]R. Cappelli, D. Maio, and D. Maltoni, “Combining Þngerprint classifiers,” in Proc. Fist Int. Workshop Multiple ClassiÞer Systems, 2000, pp. 351–361.
[23]Ross, K. Nandakumar, and A. Jain, Handbook of Multibiometrics (International Series on Biometrics). Secaucus, NJ: Springer-Verlag, 2006.