Fuzzy Local Mean Discriminant Analysis for Dimensionality Reduction (original) (raw)
Belhumeur P, Hespanha J, Kriegman D (1997) Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans Pattern Anal Mach Intell 19(7):711–720 Article Google Scholar
Lai Z, Xu Y, Chen Q, Yang J, Zhang D (2014) Multilinear sparse principal component analysis. IEEE Trans Neural Netw Learn Syst 25(10):1942–1950 Article Google Scholar
Tenenbaum J, deSilva V, Langford J (2000) A global geometric framework for nonlinear dimensionality reduction. Science 290:2319–2323 Article Google Scholar
Roweis S, Saul L (2000) Nonlinear dimensionality reduction by locally linear embedding. Science 290:2323–2326 Article Google Scholar
Zhang Z, Zha H (2004) Paincipal manifolds and nonlinear dimensionality reduction via tangent space alignmen. SIAM J Sci Comput 26(1):313–338 ArticleMathSciNetMATH Google Scholar
Belkin M, Niyogi P (2003) Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput 15(6):1373–1396 ArticleMATH Google Scholar
He X, Niyogi P (2003) Locality Preserving Projections. In: Proceedings of 16th conference neural information processing systems
He X, Yan S, Hu Y, Niyogi P, Zhang H (2005) Face recognition using Laplacianfaces. IEEE Trans Pattern Anal Mach Intell 27(3):328–340 Article Google Scholar
Yang J, Zhang D, Yang J, Niu B (2007) Globally maximizing, locally minimizing: unsupervised discriminant projection with applications to face and palm biometrics. IEEE Trans Pattern Anal Mach Intell 29(4):650–664 Article Google Scholar
Lai Z, Jin Z, Yang J (2011) Sparse two dimensional local discriminant projections for feature extraction. Neurocomputing 74(4):629–637 Article Google Scholar
Xie S, Yang L, Yang J, Zhou G, Xiang Y (2012) Time-frequency approach to underdetermined blind source separation. IEEE Trans Neural Netw Learn Syst 23(2):306–316 Article Google Scholar
He ZS, Cichocki A, Xie SL, Choi K (2010) Detecting the number of clusters in n-way probabilistic clustering. IEEE Trans Pattern Anal Mach Intell 32(11):2006–2021 Article Google Scholar
He Z, Xie S, Zdunek R, Zhou Guoxu, Cichocki Andrzej (2011) Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering. IEEE Trans Neural Netw 22(12):2117–2131 Article Google Scholar
Agrawal A, Choubey A, Nagwanshi K K (2011) Development of adaptive fuzzy based Image Filtering techniques for efficient Noise Reduction in Medical Images. Published in Aneesh Agrawal et al,/(ijcsit) international journal of computer science and Information technologies 2(4): 1457–1461
Kerre EE, Nachtegael M (eds) (2013) Fuzzy techniques in image processing, vol 52. Physica, Springer Google Scholar
Van De Ville D, Nachtegael M, Van der Weken D, Kerre EE, Philips W, Lemahieu I (2003) Noise reduction by fuzzy image filtering. IEEE Trans Fuzzy Syst 11(4):429–436 Article Google Scholar
Schulte S, De Witte V, Nachtegael M, Van der Weken D, Kerre EE (2007) Fuzzy random impulse noise reduction method. Fuzzy Sets Syst 158(3):270–283 ArticleMathSciNet Google Scholar
Kwan HK, Cai Y (2002, August) Fuzzy filters for image filtering. In Circuits and Systems, 2002. MWSCAS-2002. The 2002 45th Midwest Symposium on 3:III-672
Othman A, Tizhoosh HR, Khalvati F (2014) EFIS–evolving fuzzy image segmentation. IEEE Trans Fuzzy Syst 22(1):72–82 Article Google Scholar
Oke OA, Adedeji TO, Alade OM, Adewusi EA (2012) Fuzzy kc-means clustering algorithm for medical image segmentation. J Inf Eng Appl 2(6):21–32 Google Scholar
Moghaddamzadeh A, Bourbakis N (1994, June) A fuzzy technique for image segmentation of color images. In: Proceedings of the Third IEEE Conference on Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence, pp 83-88
Pham DL, Prince JL (1999) An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities. Pattern Recognit Lett 20(1):57–68 ArticleMATH Google Scholar
Perez-Ornelas F, Mendoza O, Melin P, Castro JR, Rodriguez-Diaz A, Castillo O (2015) Fuzzy Index to evaluate edge detection in digital images. PLoS One 10(6):e0131161 Article Google Scholar
Verma OP, Hanmandlu M, Sultania AK, Parihar AS (2013) A novel fuzzy system for edge detection in noisy image using bacterial foraging. Multidimens Syst Signal Process 24(1):181–198 ArticleMathSciNetMATH Google Scholar
Aborisade DO (2011) Novel fuzzy logic based edge detection technique. Int J Adv Sci Technol 29:75–82 Google Scholar
Biswas R, Sil J (2012) An improved canny edge detection algorithm based on type-2 fuzzy sets. Procedia Technol 4:820–824 Article Google Scholar
Verma OP, Gumber R (2013) Simple fuzzy rule based edge detection. J Inf Process Syst 9(4):575–591 Article Google Scholar
Law T, Itoh H, Seki H (1996) Image filtering, edge detection, and edge tracing using fuzzy reasoning. IEEE Trans Pattern Anal Mach Intell 18(5):481–491 Article Google Scholar
Pal SK, King R (1983) On edge detection of X-ray images using fuzzy sets. IEEE Trans Pattern Anal Mach Intell 1:69–77 Article Google Scholar
Kuo YH, Lee CS, Liu CC (1997, July) A new fuzzy edge detection method for image enhancement. In: Proceedings of the 6th IEEE International conference on Fuzzy systems 2: 1069–1074
Tizhoosh HR (2002) Fast fuzzy edge detection. In: Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society, IEEE – NAFIPS 239-242
Becerikli Y, Karan TM (2005) A new fuzzy approach for edge detection. computational intelligence and bioinspired systems. LNCS, Springer Verlag, Berlin, pp 943–951
Ganji MF, Abadeh MS (2011) A fuzzy classification system based on ant colony optimization for diabetes disease diagnosis. Expert Syst Appl 38(12):14650–14659 Article Google Scholar
Ammari FT, Lu J, Aburrous M (2014) Intelligent banking XML encryption using effective fuzzy classification. Elsevier, London, pp 593–623 Google Scholar
Aburrous M, Khelifi A (2013, March) Phishing detection plug-in toolbar using intelligent Fuzzy-classification mining techniques. In The international conference on soft computing and software engineering [SCSE’13], San Francisco State University, San Francisco, California, USA
Keller J (1985) A fuzzy k-nearest neighbor algorithm. IEEE Trans Syst Man Cybern 15(4):580–585 Article Google Scholar
Kw K, Pedry W (2005) Face recognition using a fuzzy fisher classifier. Pattern Recognit 38(10):1717–1732 Article Google Scholar
James EA, Annadurai S (2012) An efficient implementation of weighted Fuzzy Fisherface Algorithm for face recognition using wavelet transform. J Comput Sci 8(1):6 Article Google Scholar
Khoukhi A, Ahmed SF (2011) A genetically modified fuzzy linear discriminant analysis for face recognition. J Frankl Inst 348(10):2701–2717 ArticleMATH Google Scholar
Taghlidabad M, Salehi N, Kasaei S (2011) Fuzzy regularized linear discriminant analysis for face recognition. In: Proceedings of SPIE8349, fourth international conference on machine vision (ICMV 2011): machine vision, image processing, and pattern analysis, 83491N
Li W, Ruan Q, Wan J (2013) Fuzzy nearest feature line-based manifold embedding for facial expression recognition. J Inf Sci Eng 29(2):329–346 Google Scholar
Ye J, Jin Z (2013) Non-negative matrix factorisation based on fuzzy K nearest neighbour graph and its applications. IET Comput Vis 7(5):346–353 Article Google Scholar
Wan M, Yang G, Lai Z, Jin Z (2011) Feature extraction based on fuzzy local discriminant embedding with applications to face recognition. IET Comput Vis 5(5):301–308 ArticleMathSciNet Google Scholar
Zhao C, Lai Z, Liu C, Gu X, Qian J (2012) Fuzzy local maximal marginal embedding for feature extraction. Soft Comput 16(1):77–87 Article Google Scholar
Yang W, Yan X, Zhang L, Sun C (2010) Feature extraction based on fuzzy 2DLDA. Neurocomputing 73:1556–1561 Article Google Scholar
Zheng Y, Yang J, Wu X, Li Y (2007) A new two-dimensional linear discriminant analysis algorithm based on fuzzy set theory. Eng Sci 9(2):49–53 Google Scholar
Wu X, Zhou J (2013) Fuzzy two-dimensional local graph embedding discriminant analysis (F2DLGEDA) with its application to face and palm biometrics. Neural Comput Appl 23(1):201–207 Google Scholar
Ye J, Janardan R, Li Q (2004) Two-dimensional linear discriminant analysis. Adv Neural Inf Process Syst 17:1569–1576 Google Scholar
Li H, Jiang T, Zhang K (2006) Efficient and robust feature extraction by maximum margin criterion. IEEE Trans Neural Netw 17(1):157–165 Article Google Scholar
Martinez A, Benavente R (1998) The AR face database. CVC Technical Report #24
Raghavan V, Bollmann P, Jung GS (1989) A critical investigation of recall and precision as measures of retrieval system performance. ACM Trans Inf Syst 7(3):205–229 Article Google Scholar
Zhang D (2004) Palmprint authentication. Kluwer Academic, Dordrecht Google Scholar