Abstract
This paper presents a novel technique for face recognition based on facial landmarks extracted automatically. Our landmarks are those associated with eyes mouth and nose. To extract facial landmarks, we first use Haar cascade algorithm to detect the face ROI following by Haar cascade algorithm for the eye, mouth and nose ROI determination. To find landmark associated with the eye, we convert eye ROI image to binary image using thresholding algorithm. To exclude the eyebrow region, we apply horizontal radon transform. The project data will then be used to separate the eyebrow region from the eye region. To detect eye-related landmark, vertical radon transform is applied. With the vertical projection data, the outermost pixel can be identified and the associated eye landmark can be determined. The similar technique can then be used to identify landmarks associated with the nose and mouth area. Given the correspond landmarks on the reference face and the query face, geometric transformation can be determined using normal equation bases on minimized mean squared error. The two faces are then aligned. To provide the quantitative measurement, the two aligned face are converted to edge image using canny edge algorithm. The distance map error between the two aligned edge facial images is then used to identify the query face. The purposed algorithm for person identification was tested on the face database resulting in a very high accuracy.
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References
D. Bozinov and P. -M. Seidel, “Iterative gridding for automated microarray image analysis,” Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on, vol. 2, pp. 1635–1638, 7–10 Nov. 2004.
K. H. Pun and Y. S. Moon, “Recent advances in ear biometrics,” Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on, pp. 164–169, 17–19 May 2004.
P. J. Phillips, Hyeonjoon Moon, et al., “The FERET evaluation methodology for face-recognition algorithms,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 22, no. 10, pp. 10901104, Oct 2000.
S. Pankanti, S. Prabhakar and A. K. Jain, “On the individuality of fingerprints,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 24, no. 8, pp. 1010–1025, Aug 2002.
D. K. Wagg and M. S. Nixon, “On automated model-based extraction and analysis of gait,” Automatic Face and Gesture Recognition, Proceedings. Sixth IEEE International Conference on, pp. 11–16, May 2004.
R. Sanchez-Reillo, C. Sanchez-Avila and A. Gonzalez-Marcos, “Biometric identification through hand geometry measurements,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 22, no. 10, pp. 1168–1171, Oct 2000.
Lye Wil Liam, A. Chekima, Liau Chung Fan and J. A. Dargham, “Iris recognition using self-organizing neural network,” Research and Development, 2002. SCOReD 2002. Student Conference on, pp. 169172, 2002.
Enzhe Yu and Sungzoon Cho, “GA-SVM wrapper approach for feature subset selection in keystroke dynamics identity verification,” Neural Networks, 2003. Proceedings of the International Joint Conference on, vol. 3, pp. 2253–2257, 20–24 July 2003.
T. Nakamoto and T. Moriizumi, “Odor sensor using quartz-resonator array and neural-network pattern recognition,” Ultrasonics Symposium, 1988. Proceedings., IEEE 1988, vol. 1, pp. 613–616, 2–5 Oct 1988.
Lei Zhang and D. Zhang, “Characterization of palmprints by wavelet signatures via directional context modeling,” Systems, Man, and Cybernetics, Part B: IEEE Transactions on, vol. 34, no. 3, pp. 13351347, June 2004.
P. J. Besl, “Geometric modeling and computer vision,” Proceedings of the IEEE, vol. 76, no. 8, pp. 936–958, Aug 1988.
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Juhong, A., Purahong, B., Suwan, S., Pitavirooj, C. (2019). Biometrics Based on Facial Landmark with Application in Person Identification. In: Lhotska, L., Sukupova, L., Lacković, I., Ibbott, G.S. (eds) World Congress on Medical Physics and Biomedical Engineering 2018. IFMBE Proceedings, vol 68/1. Springer, Singapore. https://doi.org/10.1007/978-981-10-9035-6_30
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DOI: https://doi.org/10.1007/978-981-10-9035-6_30
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