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Matching Forensic Sketches to Mug Shot Photos Using a Population of Sketches Generated by Combining Geometrical Facial Changes and Genetic Algorithms
Matching mug shot photos to forensic sketches drawn according to verbal descriptions of eyewitnesses is a decisive point for criminal investigations. However, the incapability of a witness to precisely describe the appearance of a suspect and his/her reliance on a subjective aspect of the description often lead to imprecise and inadequate sketches. This necessitates the development of robust automated matching methods such that least dependency exists on the quality of original sketches. The focus of the paper is on enhancing the preprocessing phase, before the matching phase is applied, by generating a population of sketches out of each initial sketch via applying geometrical changes in facial areas. The population is then optimized using Genetic Algorithms (GA) by adopting the Structural SIMilarity (SSIM) index as the fitness function. The matching is finally applied to the best sketch produced by GA by employing the Local Feature-based Discriminant Analysis (LFDA) framework. The efficiency of the proposed hybrid approach in achieving correct matchings is evaluated against 88 sketch/photo pairs provided by the Michigan State Police Department and Forensic Art Essentials, and 100 sketch/black-and-white photo pairs from FERET database. The experimental results indicate that our proposed approach obtains fairly better results relative to the LFDA framework. Furthermore, we notice a significant improvement in the retrieval rate if sketch/photo pairs are first cropped to central facial areas before a matching technique is applied.
Keywords
Face Recognition, Forensic Sketch, Population of Sketches, Geometrical Facial Changes, Genetic Algorithms, Central Facial Areas.
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- X. Tang and X. Wang, Face Sketch Recognition. IEEE Transactions on Circuits and Systems for Video Technology, 2004. 14(1): p. 50-57.
- D. Lin and X. Tang, Inter-Modality Face Recognition, in Proc. European Conference Computer Vision, 2006.
- X. Wang and X. Tang, Face Photo-Sketch Synthesis and Recognition, IEEE Transactions Pattern Analysis and Machine Intelligence, 2009. 31(11): p. 1955-1967.
- G. A. Kukhareva, Y.N.M., and N. L. Shchegolevac, New Solutions for Face Photo Retrieval Based on Sketches,. Pattern Recognition and Image Analysis, 2016. 26(1): p. 165–175.
- Z z. Wang and A. C. Bovik, A universal image quality index,. IEEE Signal Processing Lett., 2002. 9(3): p. 81–84.
- Brendan F. Klare, Zz.L.a.A.K.J., Matching Forensic Sketches to Mug Shot Photos, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011. 33(3): p. 639-646.
- Michigan State Police Department, http://www.michigan.gov/msp/.
- L. Gibson, Forensic Art Essentials. 2008: Elsevier.
- R. Uhl and N. Lobo, A Framework for Recognizing a Facial Image from a Police Sketch, in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1996.
- W. Konen, Comparing facial line drawings with gray-level images: A case study on PHANTOMAS,, in International Conference Bochum, Germany. 1996. p. 727–734.
- D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints. Int’l J. Computer Vision, 2004. 60(2): p. 91-110.
- Timo Ahonen, A.H., and Matti Pietika¨ inen, Face Description with Local Binary Patterns: Application to Face Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006. 28(12).
- Anil K. Jain, B.K.a.U.P., Face Recognition: Some Challenges in Forensics, in IEEE Int'l Conference on Automatic Face and Gesture Recognition, 2011.
- Hu Han, B.F.K., Kathryn Bonnen, and Anil K. Jain, Matching Composite Sketches to Face Photos: A Component-Based Approach. IEEE Transactions on Information Forensics and Security, 2013. 8(1): p. 191-204.
- S. Klum, H.H., Anil K. Jain and B. Klare, Sketch Based Face Recognition: Forensic vs. Composite Sketches, in Biometrics (ICB), International Conf. 2013: Madrid, Spain.
- B. Klare and A. Jain, Sketch to Photo Matching: A Feature-Based Approach, Proc. SPIE Conf. Biometric Technology for Human Identification VII, 2010.
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