Abstract
In this paper, we present a general framework for a combination of shape (shape Trace transform-STT) and texture (masked Trace transform-MTT) classifiers based on the features derived from the Trace transform. The MTT offers “texture” representation which is used to reduce the within-class variance, while STT provides “shape” characteristics which helps us maximize the between-class variance. In addition, weighted Trace transform (WTT) identifies the tracing lines of the MTT which produce similar values irrespective of intraclass variations. Shape and texture are integrated by a classifier combination algorithm. Our system is evaluated with experiments on the XM2VTS database using 2,360 face images.
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References
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© 2004 Springer-Verlag Berlin Heidelberg
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Srisuk, S., Petrou, M., Fooprateep, R., Sunat, K., Kurutach, W., Chopaka, P. (2004). A Combination of Shape and Texture Classifiers for a Face Verification System. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_7
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DOI: https://doi.org/10.1007/978-3-540-25948-0_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22146-3
Online ISBN: 978-3-540-25948-0
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