Abstract
In this paper, a new method for face and palmprint recognition has been proposed based on hierarchical multiscale local binary pattern (HMLBP) and adaptive LBP with directional statistical features (ALBPF) methods. It’s build a hierarchical multiscale ALBPF histogram for an image. By using HMLBP, the representative features of “non-uniform” patterns are extracted at a smaller scale. On the other hand, using ALBPF improves the efficiency by incorporating mean and standard deviation statistical features in addition to minimizing the directional difference along different orientation .The results of experiments conducted on 2 public face databases and 2 public palmprint databases show that our proposed method has better recognition accuracy than LBP, ALBPF and HMLBP methods.
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Shams, G., Ismail, M., Bassiouny, S., Ghanem, N. (2014). Face and Palmprint Recognition Using Hierarchical Multiscale Adaptive LBP with Directional Statistical Features. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_12
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DOI: https://doi.org/10.1007/978-3-319-11755-3_12
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