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14 December 2015 Study on local Gabor binary patterns for face representation and recognition
Wei Ge, Chunling Han, Wei Quan
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Proceedings Volume 9813, MIPPR 2015: Pattern Recognition and Computer Vision; 981316 (2015) https://doi.org/10.1117/12.2209430
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
More recently, Local Binary Patterns(LBP) has received much attention in face representation and recognition. The original LBP operator could describe the spatial structure information, which are the variety edge or variety angle features of local facial images essentially, they are important factors of classify different faces. But the scale and orientation of the edge features include more detail information which could be used to classify different persons efficiently, while original LBP operator could not to extract the information. In this paper, based on the introduction of original LBP-based facial representation and recognition, the histogram sequences of local Gabor binary patterns are used to representation facial image. Principal Component Analysis (PCA) method is used to classification the histogram sequences, which have been converted to vectors. Recognition experimental results show that the method we used in this paper increases nearly 6% than the classification performance of original LBP operator.
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Wei Ge, Chunling Han, and Wei Quan "Study on local Gabor binary patterns for face representation and recognition", Proc. SPIE 9813, MIPPR 2015: Pattern Recognition and Computer Vision, 981316 (14 December 2015); https://doi.org/10.1117/12.2209430
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KEYWORDS
Binary data
Facial recognition systems
Principal component analysis
Image classification
Independent component analysis
Wavelets
Image filtering
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