Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Multiresolution Histograms and Their Use for Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Competitive Coding Scheme for Palmprint Verification
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Ordinal Palmprint Represention for Personal Identification
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Review article: Touch-less palm print biometrics: Novel design and implementation
Image and Vision Computing
Palmprint recognition based on directional features and graph matching
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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Recent literatures have revealed that statistics of local texture measures can provide accurate descriptions of palmprint appearances. In this framework, one palmprint image is divided into local blocks with multiple spatial resolutions. The statistical texture descriptions of each block are then concatenated to form a multi-scale image representation. However, resultant high-dimensional statistical features lead to increasing of computational cost. In this paper, we tackle this problem by performing a coarse-to-fine cascade scheme, which makes use of information redundancy of statistical texture descriptions between different spatial scales. In contrast with non-cascade strategies, the proposed method reduces most of computational burden and achieves accurate classification simultaneously.