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Finger-Knuckle-Print Recognition System Based on Features-level Fusion of Real and Imaginary Images
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In this paper, a new method based on Log Gabor- TPLBP (LGTPLBP) has been proposed. However the Three Patch Local Binary Patterns (TPLBP) technique used in face recognition has been applied in Finger-Knuckle-Print (FKP) recognition. The 1D- Log Gabor filter has been used to extract the real and the imaginary images from each of the Region of Interest (ROI) of FKP images. Then the TPLBP descriptor on both images has been applied to extract the feature vectors of the real image and the imaginary image respectively. These feature vectors have been jointed to form a large feature vector for each image FKP. After that, the obtained feature vectors of all images are processed directly with a dimensionality reduction algorithm, using linear discriminant analysis (LDA). Finally, the cosine Mahalanobis distance (MAH) has been used for matching stage. To evaluate the effectiveness of the proposed system several experiments have been carried out. The Hong Kong Polytechnic University (PolyU) FKP database has been used during all of the tests. Experimental results show that the introduced system achieves better results than other state-of-the-art systems for both verification and identification.
Keywords
Biometric Systems, Three Patch Local Binary Patterns, 1D Log Gabor Filter, Finger Knuckle Print.
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- D. Maltoni, D. Maio, A.K. Jain and S. Prabhakar, “Handbook of Fingerprint Recognition”, Springer, 2003.
- Q. Zhao, D. Zhang, L. Zhang and N. Luo, “Adaptive Fingerprint Pore Modeling and Extraction”, Pattern Recognition, Vol. 43, No. 8, pp. 2833-2844, 2010.
- G. Jaswal, A. Nigam and R. Nath, “DeepKnuckle: Revealing the Human Identity”, Multimedia Tools and Applications, Vol. 76, No. 18, pp. 18955-18984, 2017.
- W. Jia, D. Huang and D. Zhang, “Palmprint Verification based on Robust Line Orientation Code”, Pattern Recognition, Vol. 41, No. 5, pp. 1504-1513, 2008.
- Z. Guo, D. Zhang, L. Zhang and W. Zuo, “Palmprint Verification using Binary Orientation Co- Occurrence Vector”, Pattern Recognition Letters, Vol. 30, No. 13, pp. 1219-1227, 2009.
- W. Zhao, R. Chellappa, P.J. Phillips and A. Rosenfeld, “Face Recognition: A Literature Survey”, ACM Computing Surveys, Vol. 35, No. 4, pp. 339-458, 2003.
- J. Daugman, “How Iris Recognition Works”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 1, pp. 21-30, 2004.
- W. Dong, Z. Sun and T. Tan, “Iris Matching based on Personalized Weight Map”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 9, pp. 1744-1757, 2011.
- A. Uhl and P. Wild, “Footprint-based Biometric Verification”, Journal of Electronic Imaging-Society of Photo-Optical Instrumentation Engineers, Vol. 17, No. 1, pp. 110-116, 2008.
- L. Zhang, L. Zhang, D. Zhang and H. Zhu, “Online FingerKnuckle-Print Verification for Personal Authentication”, Pattern Recognition, Vol. 43, No. 7, pp. 2560-257, 2010.
- A. Kumar and Ch. Ravikanth, “Personal Authentication using Finger Knuckle Surface”, IEEE Transactions on Information Forensics and Security, Vol. 4, No. 1, pp. 98-109, 2009.
- S. Prabhakar, and A.K. Jain, “Decision-Level Fusion in Fingerprint Verification”, Pattern Recognition, Vol. 35, No. 4, pp. 861-874, 2002.
- A. Meraoumia, S. Chitroub and A. Bouridane, “Palmprint and Finger-Knuckle-Print for Efficient Person Recognition based on Log-Gabor Filter Response”, Analog Integrated Circuits and Signal Processing, Vol. 69, No. 2, pp.17-27, 2011.
- K.A. Toh, X. Jiang and W.Y. Yau, “Exploiting Global and Local Decisions for Multimodal Biometrics Verification”, IEEE Transactions on Signal Processing, Supplement on Secure Media, Vol. 52, No. 10, pp. 3059-3072, 2004.
- A. Ross, D. Nandakumar, and A.K. Jain, “Handbook of Multibiometrics”, Springer, 2006.
- G. Gao, J. Yang, J. Qian and L. Zhang, “Integration of Multiple Orientation and Texture Information for FingerKnuckle-Print Verification”, Neurocomputing, Vol. 135, pp. 180-191, 2014.
- Z.S. Shariatmadar and K. Faez, “An Efficient Method for Finger Knuckle- Print Recognition by using the Information Fusion at Different Levels”, Proceedings of IEEE International Conference on Hand-Based Biometrics, pp. 1-6, 2011.
- L. Zichao, K. Wang and W. Zuo, “Finger-Knuckle-Print Recognition using Local Orientation Feature based on Steerable Filter”, Proceedings of International Conference on Intelligent Computing, Vol. 304, pp. 224-230, 2012.
- W. El-Tarhouni, M.K. Shaikh, L. Boubchir and A. Bouridane, “Multi-Scale Shift Local Binary Pattern BasedDescriptor for Finger-Knuckle-Print Recognition”, Proceedings of 26th International Conference on Microelectronics, pp. 408-413, 2014.
- B. Zeinali, A. Ayatollah and M. Kakooei, “A Novel Method of Applying Directional Filter Bank for Finger-KnucklePrint Recognition”, Proceeding of 22nd Iranian Conference on Electrical Engineering, pp. 500-504, 2014.
- M. Chaa, N. Boukezzoula and A. Meraoumia, “FeaturesLevel Fusion of Reflectance and Illumination Images in Finger-Knuckle-Print Identification System”, International Journal on Artificial Intelligence Tools, Vol. 27, No. 3, pp. 1-10, 2018.
- P.N. Belhumeur, J.P. Hespanha and D.J. Kriegman, “Eigenfaces vs. Fisherfaces: Recognition using Class Specific Linear Projection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, pp. 711-720, 1997.
- FKP Database, Available at: http://www4.comp.polyu.edu.hk/~biometrics/FKP.htm, Accessed on 2010.
- D.J. Fiel, “Relations between the Images and the Response Properties of Cortical Cells”, Journal of the Optical Society of America A, Optics and Image Science, Vol. 4, No. 2, pp. 2379-2394, 1987.
- L. Wolf, T. Hassner and Y. Taigman, “Descriptor based Methods in Wild.in Real-Life Images”, Proceedings of European Conference on Computer Vision, pp. 12-17, 2008
- S.Z. Shariatmadar and K. Faez, “Finger-Knuckle-Print Recognition via Encoding Local-Binary-Pattern”, Journal of Circuits, Systems and Computers, Vol. 22, No. 6, pp. 1-16, 2013.
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