基于L1-范數(shù)的二維線性判別分析
doi: 10.11999/JEIT141093
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61202228)和安徽省高校自然科學(xué)研究重點(diǎn)項(xiàng)目(KJ2012A004)資助課題
L1-norm Based Two-dimensional Linear Discriminant Analysis
-
摘要: 為了避免圖像數(shù)據(jù)向量化后的維數(shù)災(zāi)難問(wèn)題，以及增強(qiáng)對(duì)野值(outliers)及噪聲的魯棒性，該文提出一種基于L1-范數(shù)的2維線性判別分析(L1-norm-based Two-Dimensional Linear Discriminant Analysis, 2DLDA-L1)降維方法。它充分利用L1-范數(shù)對(duì)野值及噪聲的強(qiáng)魯棒性，并且直接在圖像矩陣上進(jìn)行投影降維。該文還提出一種快速迭代優(yōu)化算法，并給出了其單調(diào)收斂到局部最優(yōu)的證明。在多個(gè)圖像數(shù)據(jù)庫(kù)上的實(shí)驗(yàn)驗(yàn)證了該方法的魯棒性與高效性。
-
關(guān)鍵詞:
- 圖像處理 /
- L1-范數(shù) /
- 2維線性判別分析 /
- 線性投影 /
- 降維
Abstract: To overcome the curse of dimensionality caused by vectorization of image matrices, and to increase robustness to outliers, L1-norm based Two-Dimensional Linear Discriminant Analysis (2DLDA-L1) is proposed for dimensionality reduction. It makes full use of strong robustness of L1-norm to outliers and noises. Furthermore, it performs dimensionality reduction directly on image matrices. A rapid iterative optimization algorithm, with its proof of monotonic convergence to local optimum, is given. Experiments on several public image databases verify the robustness and the effectiveness of the proposed method. -
Duda R, Hart P, and Stork D. Pattern Classification[M]. Second edition, New York: John Wiley Sons, 2001: 2-5. Chan L, Salleh S, Ting C, et al.. Face identification and verification using PCA and LDA[C]. International Symposium on Information Technology, Kuala Lumpur, Malaysia, 2008: 1-6. Rujirakul K, So-In C, Arnonkijpanich B, et al.. PFP-PCA: parallel fixed point PCA face recognition[C]. 2013 4th International Conference on Intelligent Systems, Modelling and Simulation, Bangkok, 2013: 29-31. Belhumeur P, Hespanha J, and Kriegman D. Eigenfaces vs. fisherfaces: recognition using class specific linear projection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7): 711-720. Yang Jian, Zhang D, Frangi A, et al.. Two-dimensional PCA: a new approach to appearance-based face representation and recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(1): 131-137. Wang Shi-min, Ye Ji-hua, and Ying De-quan. Research of 2DPCA principal component uncertainty in face recognition[C]. 2013 8th International Conference on Computer Science Education, Colombo, Sri Lanka, 2013: 159-162. Li Ming and Yuan Bao-zong. A novel statistical linear discriminant analysis for image matrix: two-dimensional Fisherfaces[J]. Pattern Recognition Letters, 2005, 26(5): 527-532. Mahanta M and Plataniotis K. Ranking 2DLDA features based on fisher discriminance[C]. IEEE International Conference on Acoustic, Speech and Signal Processing, Florence, Italy, 2014: 4-9. Wang Bin-bin, Hao Xin-jie, Chen Li-sheng, et al.. Face recognition based on the feature fusion of 2DLDA and LBP[C]. 2013 Fourth International Conference on Information, Intelligence, Systems and Applications, Piraeus, Greece, 2013: 10-12. Pang Yan-wei, Li Xue-long, and Yuan Yuan. Robust tensor analysis with L1-norm[J]. IEEE Transactions on Circuits Syst ems for Video Techology, 2010, 20(2): 172-178. Zheng Wen-ming, Lin Zhou-chen, and Wang Hai-xian. L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction[J]. IEEE Transactions on Neural Networks and Learning Systems, 2014, 25(4): 793-805. Kwak N. Principal component analysis based on L1-norm maximization[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(9): 1672-1680. Li Xi, Hu Wei-ming, Wang Han-zi, et al.. Linear discriminant analysis using rotational invariant L1 norm[J]. Neurocomputing, 2010, 73(13): 2571-2579. Wang Hai-xian, Lu Xue-song, Hu Zi-lan, et al.. Fisher discriminant analysis with L1-norm[J]. IEEE Transactions on Cybernetics, 2013, 44(6): 828-842. Zhong Fu-jin and Zhang Jia-shu. Linear discriminant analysis based on L1-norm maximization[J]. IEEE Transactions on Image Processing, 2013, 22(8): 3018-3027. Li Xue-long, Pang Yan-wei, and Yuan Yuan. L1-norm-based 2DPCA[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2010, 40(4): 1170-1175. Wang Hai-xian, Tang Qin, and Zheng Wen-ming. L1-norm- based common spatial patterns[J]. IEEE Transactions on Biomedical Engineering, 2012, 59(3): 653-662. Jenatton R, Obozinski G, and Bach F. Structured sparse principal component analysis[C]. International Conference on Artificial Intelligence and Statistics, Paris, France, 2009: 1-8. Gross R, Matthews I, Cohn J, et al.. Multi-PIE[C]. 8th IEEE International Conference on Automatic Face Gesture Recognition, Amsterdam, The Netherland, 2008: 1-8. Martinez A and Benavente R. The AR face database[R]. CVC Technical Report 24, Barcelona, Spain, 1998. Samaria F and Harter A. Parameterisation of a stochastic model for human face identification[C]. Proceedings of the Second IEEE Workshop on Applications of Computer Vision, Sarasota, USA, 1994, 138-142. -
計(jì)量
- 文章訪問(wèn)數(shù): 2047
- HTML全文瀏覽量: 245
- PDF下載量: 897
- 被引次數(shù): 0
下載:
