The pixel-based shape representation has been sensitive to rotation. In this paper, we propose a pixel-based descriptor that is invariant with rotation and scale for the hand shape recognition in Taiwanese Sign Language (TSL). Based on the property that a hand shape is characteristic of a unique pointing direction, angle normalization is used to meet the rotation-invariant requirement. With angle normalization, the traces of class covariance matrices have been reduced almost all over the classes of hand shapes, implying a less overlap between classes. It is confirmed by the experiments that show an increase in recognition accuracy. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Huang, J. N., Hsieh, P. F., & Wu, C. H. (2005). Vision-based recognition of hand shapes in taiwanese sign language. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3784 LNCS, pp. 224–231). Springer Verlag. https://doi.org/10.1007/11573548_29
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