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Gabor特征集结合判别式字典学习的稀疏表示图像识别

DOI: 10.11834/jig.20130209

Keywords: 稀疏表示,稀疏模式分类,Gabor特征,Fisher字典学习

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Abstract:

稀疏编码中字典的选择无论对图像重建还是模式分类都有重要影响,为此提出Gabor特征集结合判别式字典学习的稀疏表示图像识别算法。考虑到Gabor局部特征对光照、表情和姿态等变化的鲁棒性,首先提取图像对应不同方向、不同尺度的多个Gabor特征;然后将降维的增广Gabor特征矩阵作为初始特征字典,通过对该字典的学习得到字典原子对应类别标签的新结构化字典,新字典中特定类的子字典对相关的类具有好的表示能力,同时应用Fisher判别约束编码系数,使它们具有小的类内散度和大的类间散度;最后同时用具有判别性的重构误差和编码系数来进行模式分类。基于3个数据库的实验结果表明本文方法具有可行性和有效性。

References

[1]  Wright J, Yang A Y, Ganesh A, et al. Robust face recognition via sparse representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(2): 210-227.
[2]  Yang M, Zhang L, Yang J, et al. Metaface learning for sparse representation based face recognition[C]//Proceedings of the International Conference on Image Processing. Hong Kong, China: IEEE Signal Processing Society, 2010: 1601-1604.
[3]  Ramírez I, Sprechmann P, Sapiro G. Classification and clustering via dictionary learning with structured incoherence and shared features[C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. California, USA:IEEE Computer Society, 2010: 3501-3508.
[4]  Zhang Q, Li B X. Discriminative K-SVD for dictionary learning in face recognition[C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. California, USA:IEEE Computer Society, 2010:2691-2698.
[5]  Mailhé B, Plumbley M D. Dictionary learning with large step gradient descent for sparse representations[C]//Proceedings of International Conference on Latent Variable Analysis and Signal Separation.Tel-Aviv, Israel:Springer,2012:231-238.
[6]  Aharon M, Elad M, Bruckstein A. K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Transactions on Signal Processing, 2006,54(11):4311-4322.
[7]  Jiang Z L, Lin Z, Davis L S. Learning a discriminative dictionary for sparse coding via label consistent K-SVD[C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Colorado Springs,USA:IEEE Computer Society, 2011:1697-1704.
[8]  Ramirez I, Sapiro G. Sparse coding and dictionary learning based on the MDL principle[C]//Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. Prague, Czech Republic:IEEE, 2011:2160-2163.
[9]  Yang M, Zhang L, Feng X C, et al. Fisher discrimination dictionary learning for sparse representation[C]//Proceedings of IEEE International Conference on Computer Vision. Barcelona, Spain: IEEE, 2011:543-550.
[10]  Porat M, Zeevi Y. The generalized Gabor scheme of image representation in biological and machine vision[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1988,10(4):452-468.
[11]  Wiskott L, Fellous J M, Kruger N, et al. Face recognition by elastic bunch graph matching[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1997,19(7):775-779.
[12]  Yang M, Zhang L. Gabor feature based sparse representation for face recognition with Gabor occlusion dictionary[C]//Proceedings of the 11th European Conference on Computer Vision. Crete, Greece: Springer,2010: 448-461.
[13]  Liu C J, Wechsler H. Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition[J].IEEE Trans. on Image Processing, 2002,11(4):467-476.
[14]  Zhang W C, Shan S G,Zhang H M,et al. Histogram sequence of local Gabor Binary Pattern for face description and identification[J].Journal of Software,2006,17(12): 2508-2517.[张文超,山世光,张洪明,等.基于局部Gabor变化直方图序列的人脸描述与识别[J]. 软件学报, 2006,17(12):2508-2517]

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