CFP last date
20 January 2025
Reseach Article

3D Face Recognition Using Radon Transform and Symbolic LDA

by P. S. Hiremath, Manjunath Hiremath
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 67 - Number 4
Year of Publication: 2013
Authors: P. S. Hiremath, Manjunath Hiremath
10.5120/11380-6666

P. S. Hiremath, Manjunath Hiremath . 3D Face Recognition Using Radon Transform and Symbolic LDA. International Journal of Computer Applications. 67, 4 ( April 2013), 1-4. DOI=10.5120/11380-6666

@article{ 10.5120/11380-6666,
author = { P. S. Hiremath, Manjunath Hiremath },
title = { 3D Face Recognition Using Radon Transform and Symbolic LDA },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 67 },
number = { 4 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume67/number4/11380-6666/ },
doi = { 10.5120/11380-6666 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:23:44.353528+05:30
%A P. S. Hiremath
%A Manjunath Hiremath
%T 3D Face Recognition Using Radon Transform and Symbolic LDA
%J International Journal of Computer Applications
%@ 0975-8887
%V 67
%N 4
%P 1-4
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Many recent events, such as terrorist attacks, have exposed the serious weaknesses in most sophisticated security systems. Three dimensional (3D) human face recognition is emerging as a significant biometric technology. Research interest in 3D face recognition has increased during recent years due to the availability of improved 3D acquisition devices and processing algorithms. In this paper, the novel method for three dimensional (3D) face recognition using Radon transform and Symbolic LDA based features of 3D range face images is proposed. In this method, the Symbolic LDA based feature computation takes into account the face image variations to a larger extent and has the advantage of dimensionality reduction. The experimental results have yielded 99. 50% recognition performance with reduced computational cost, which compares well with other state-of-the-art methods.

References
  1. Kyong I. , Chang Kevin, W. Bowyer, Patrick J. Flynn, "Multi-Modal 2D and 3D Biometrics for Face Recognition", Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG'03) ,2003, pp. 187-194.
  2. Andrea F. Abate, Michele Nappi, Daniel Riccio, Gabriele Sabatino , "2D and 3D face recognition: A survey", Pattern Recognition Letters, Vol. 28, No. 14, 2007, Pages 1885– 1906.
  3. Shalini Gupta, Mia K. Markey, Alan C. Bovik, "Anthropometric 3D Face Recognition", Int. Journal of Computer Vision, Volu. 90, No. 3, December 2010,pp. 331-349.
  4. Xiaoguang Lu , Dirk Colbry, Anil K. Jain, "Matching 2. 5D Scans for Face Recognition", Int. Conf. Pattern Recog. (ICPR 2004), pp. 362-366.
  5. Kyong I. Chang, Bowyer, K. W. , Flynn P. J. , "Adaptive Rigid Multi-region Selection for Handling Expression Variation in 3D Face Recognition", Computer Vision and Pattern Recognition- Workshops, 2005.
  6. S. Gupta, K. R. Castleman, M. K. Markey, A. C. Bovik, "Texas 3D Face Recognition Database", IEEESouthwest Symposium on Image Analysis and Interpretation,May 2010, p 97-100, Austin, TX. URL:http://live. ece. utexas. edu/research/texas3dfr /index. htm.
  7. Amir Averbuch and Yoel Shkolnisky, "3D Fourier based discrete Radon transform", Appl. Comput. Harmon. Anal. 15 ,Elsevier Inc. , 2003, pp. 33–69. (8) M. Turk, A. Pentland, "Eigenfaces for Recognition", Journalof Cognitive Neurosicence, Vol. 3, No. 1, 1991, pp. 71-86.
  8. H. Moon, P. J. Phillips, "Computational and Performance aspectsof PCA-based Face Recognition Algorithms", Perception,Vol. 30, 2001, pp. 303-321.
  9. Bock, H. H. Diday E. (Eds) : "Analysis of Symbolic Data",Springer Verlag, 2000.
  10. Carlo N. Lauro and Francesco Palumbo, "Principal Component Analysis of Interval Data: a Symbolic Data Analysis Approach", Computational Statistics, Vol. 15, No. 1, 2000, pp. 73-87.
  11. K. Etemad, R. Chellappa, "Discriminant Analysis for Recognition of Human Face Images", Journal of the Optical Society of America, Vol. 14, No. 8, August 1997, pp. 1724-1733.
  12. P. S. Hiremath, C. J. Prabhakar, "Face Recognition Technique Using Symbolic Linear Discriminant Analysis Method", Lecture Notes in Computer Science, Vol. 4338, 2006, pp 641-649.
  13. P. S. Hiremath and Manjunath Hiremath, "3D Face RecognitionUsing Radon Transform and PCA", InternationalJournal of Graphics & Image Processing, Vol. 2, No. 2, May2012. pp. 123-128.
  14. P. S. Hiremath and Manjunath Hiremath, "Linear discriminantanalysis for 3D face recognition using radon transform",International Conference on Multimedia, Processing,Communication and Computing Applications, 13-15 December2012 (Accepted).
  15. P. S. Hiremath and Manjunath Hiremath, "3D Face RecognitionUsing Radon Transform and Symbolic PCA", InternationalJournal of Electronics and Computer Science Engineering,Vol. 1, No. 4, October 2012, pp. 2342-2349.
Index Terms

Computer Science
Information Sciences

Keywords

3D face recognition range image radon transform Symbolic LDA