Abstract
Thermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual’s signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results.
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Akhloufi, M., Bendada, A.: Infrared face recognition using distance transforms. In: Proceedings of the World Academy of Science, Engineering and Technology, vol. 30, pp. 160–163 (2008)
Andaló, F.A., Miranda, P.A.V., Torres, R.d.S., Falcão, A.X.: Shape feature extraction and description based on tensor scale. Pattern Recognition 43(1), 26–36 (2010)
Buddharaju, P., Pavlidis, I.T.: Physiological face recognition is coming of age. In: Proceedings of the Conference on Computer Vision and Pattern Recognition, pp. 128–135. IEEE Computer Society, Los Alamitos (2009)
Buddharaju, P., Pavlidis, I.T., Kakadiaris, I.A.: Face recognition in the thermal infrared spectrum. In: Proceedings of the Conference on Computer Vision and Pattern Recognition Workshop, vol. 8, pp. 167–191 (2004)
Buddharaju, P., Pavlidis, I.T., Tsiamyrtzis, P., Bazakos, M.: Physiology-based face recognition in the thermal infrared spectrum. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4), 613–626 (2007)
Chen, X., Flynn, P.J., Bowyer, K.W.: Ir and visible light face recognition. Computer Vision and Image Understanding 99(3), 332–358 (2005)
Chen, X., Flynn, P.J., Bowyer, K.W.: Ir and visible light face recognition. Computer Vision and Image Understanding 99(3), 332–358 (2005)
Falcão, A.X., da Costa, L.F., Cunha, B.S.: Multiscale skeletons by image foresting transform and its application to neuromorphometry. Pattern Recognition 35(7), 1571–1582 (2002)
Falcão, A.X., Stolfi, J., Lotufo, R.A.: The image foresting transform: Theory, algorithms, and applications. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(1), 19–29 (2004)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)
Rocha, L.M., Cappabianco, F.A.M., Falcão, A.X.: Data clustering as an optimum-path forest problem with applications in image analysis. International Journal of Imaging Systems and Technology 19(2), 50–68 (2009)
Vincent, L., Soille, P.: Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence 13(6), 583–598 (1991)
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Osaku, D., Marana, A.N., Papa, J.P. (2011). A Graph-Based Framework for Thermal Faceprint Characterization. In: Maino, G., Foresti, G.L. (eds) Image Analysis and Processing – ICIAP 2011. ICIAP 2011. Lecture Notes in Computer Science, vol 6978. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24085-0_18
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DOI: https://doi.org/10.1007/978-3-642-24085-0_18
Publisher Name: Springer, Berlin, Heidelberg
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