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Matching Composite Sketches to Facial Photos using Component-based Approach

by Archana Uphade, J.V. Shinde
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 129 - Number 15
Year of Publication: 2015
Authors: Archana Uphade, J.V. Shinde
10.5120/ijca2015907121

Archana Uphade, J.V. Shinde . Matching Composite Sketches to Facial Photos using Component-based Approach. International Journal of Computer Applications. 129, 15 ( November 2015), 17-21. DOI=10.5120/ijca2015907121

@article{ 10.5120/ijca2015907121,
author = { Archana Uphade, J.V. Shinde },
title = { Matching Composite Sketches to Facial Photos using Component-based Approach },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 129 },
number = { 15 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume129/number15/23149-2015907121/ },
doi = { 10.5120/ijca2015907121 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:23:30.441696+05:30
%A Archana Uphade
%A J.V. Shinde
%T Matching Composite Sketches to Facial Photos using Component-based Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 129
%N 15
%P 17-21
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Face recognition has an important application in criminal investigation. Previous research on sketch recognition focused on matching sketches drawn by professional artists. There has been number of representation methods are used to solve the problem of matching facial sketches to photographs. In the proposed system composite sketches are synthesized using one of the several facial composite software systems. A component-based representation (CBR) approach is used to measure the similarity between a composite sketch and mugshot photograph. First detect the facial landmarks in composite sketches and face photos using an active shape model (ASM) followed by computing length between elements. Features are then extracted for each facial component using multiscale local binary patterns (MLBPs), and per component similarity are calculated. In proposed system per component features are measured and compared with the features of the mugshot gallery set for matching. Depending on the component matching images will be display in sorted order.

References
  1. Hu Han, Brendan F. Klare, Kathryn Bonnen, and Anil K. Jain. “Matching Composite Sketches to Face Photos: A Component-Based Approach” IEEE Transactions on Information Forensics And SECURITY, VOL. 8, NO. 1, JANUARY 2013.
  2. Brendan F. Klare and Anil K. Jain.2013.“Heterogeneous Face Recognition Using Kernel Prototype Similarities”. TPAMI (2013), 1410-1422.
  3. H. Han, S. Shan, X. Chen, S. Lao, and W. Gao, “Separability oriented preprocessing for illumination-invariant face recognition,” in Proc. Eur. Conf. Computer Vision, 2012, pp. 307–320.
  4. B. Klare, Z. Li, and A. Jain, “Matching forensic sketches to mug shot photos,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 3, pp. 639–646, Mar. 2011.
  5. Handbook of Face Recognition, S. Z. Li andA.K. Jain, Eds., 2nd ed. New York: Springer, 2011.
  6. W. Zhang, X. Wang, and X. Tang, “Coupled information-theoretic encoding for face photo-sketch recognition,” in Proc. Conf. Computer Vision and Pattern Recognition, 2011, pp. 513–520.
  7. A. Sharma and D. Jacobs, “Bypassing synthesis: PLS for face recognition with pose, low-resolution and sketch,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2011, pp. 593–600.
  8. H. Han, S. Shan, L. Qing, X. Chen, and W. Gao, “Lighting aware preprocessing for face recognition across varying illumination,” in Proc. Eur. Conf. Computer Vision, 2010, pp. 308–321.
  9. X. Wang and X. Tang, “Face photo-sketch synthesis and recognition,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 11, pp. 1955–1967, Nov. 2009.
  10. X. Wang and X. Tang, “Face photo-sketch synthesis and recognition,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 11, pp. 1955–1967, Nov. 2009.
  11. Z. Lei and S. Li, “Coupled spectral regression for matching hegerogeneous faces,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition,2009, pp. 1123–1128.
  12. H. Han, S. Shan, X. Chen, and W. Gao, “Illumination transfer using homomorphic wavelet filtering and its application to light-insensitive face recognition,” in Proc. Automatic Face and Gesture Recognition, 2008, pp. 1–6.
  13. X. Gao, J. Zhong, J. Li, and C. Tian, “Face sketch synthesis algorithm based on E-HMM and selective ensemble,” IEEE Trans. Circuits Syst. Video Technol., vol. 18, no. 4, pp. 487–496, Apr. 2008.
  14. P. C. Yuen and C. H. Man. 2007.“Human Face Image Searching System Using Sketches”.IEEE Transaction on Systems, Man and Cybernetics, Part A: System and Humans (TSMC) (2007), 493-504.
  15. P. C. Yuen and C. H. Man, “Human face image searching system using sketches,” IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, vol. 37, no. 4, pp. 493–504, Jul. 2007.
  16. P. C. Yuen and C. H. Man, “Human face image searching system using sketches,” IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, vol. 37, no. 4, pp. 493–504, Jul. 2007.
  17. G.Wells and L. Hasel, “Facial composite production by eyewitnesses,” Current Directions Psychol. Sci., vol. 16, no. 1, pp. 6–10, Feb. 2007.
  18. D. Lin and X. Tang, “Inter-modality face recognition,” in Proc. Eur. Conf. Computer Vision, 2006, pp. 13–26.
  19. D. Lin and X. Tang, “Recognize high resolution faces: From macrocosm to microcosm,” in Proc. IEEE Computer Vision and Pattern Recognition, 2006, pp. 1355–1362.
  20. D. Lin and X. Tang, “Inter-modality face recognition,” in Proc. Eur. Conf. Computer Vision, 2006, pp. 13–26.
  21. D. Lin and X. Tang, “Recognize high resolution faces: From macrocosm to microcosm,” in Proc. IEEE Computer Vision and Pattern Recognition, 2006, pp. 1355–1362.
  22. P. Sinha, B. Balas, Y. Ostrovsky, and R. Russell, “Face recognition by humans: Nineteen results all computer vision researchers shouldknow about,” Proc. IEEE, vol. 94, no. 11, pp. 1948–1962, Nov. 2006.
  23. D. Mcquiston, L. Topp, and R. Malpass, “Use of facial composite systems in US law enforcement agencies,” Psychology, Crime and Law, vol. 12, no. 5, pp. 505–517, 2006.
  24. C. Frowd, D. Carson, H. Ness, D. McQuiston, J. Richardson, H. Baldwin, and P. Hancock, “Contemporary composite techniques: The impact of a forensically-relevant target delay,” Legal Criminol. Psychol., vol. 10, no. 1, pp. 63–81, Feb. 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Component-based Composite-sketch Forensic sketch Heterogeneous Modality gap.

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