Discriminant Locality Preserving Projection
نویسندگان
چکیده
In this study, we proposed an improved LPP method named Scatter-Difference Discriminant Locality Preserving Projection (SDDLPP). It considers discriminant information by maximizing the scatter-difference, which makes it have better classification capability. SDDLPP also avoids the singularity problem for the highdimensional data matrix and can be directly applied to the small sample size problem while preserving more important information. Comparative recognition performance results on public face and palmprint databases also demonstrate the effectiveness of the proposed SDDLPP approach.
منابع مشابه
Optimized Discriminant Locality Preserving Projection of Gabor Feature for Biometric Recognition
Discriminant locality preserving projection(DLPP) can not obtain optimal discriminant vectors which utmostly optimize the objective of DLPP. This paper proposed a Gabor based optimized discriminant locality preserving projections (ODLPP) algorithm which can directly optimize discriminant locality preserving criterion on high-dimensional Gabor feature space via simultaneous diagonalization, with...
متن کاملGabor Based Optimized Discriminant Locality Preserving Projection for Feature Extraction and Recognition
This paper proposed a Gabor based optimized discriminant locality preserving projections (ODLPP) algorithm which can directly optimize discriminant locality preserving criterion on high-dimensional Gabor feature space via simultaneous diagonalization, without any dimensionality reduction preprocessing. Experimental results conducted on the VALID face database indicate the effectiveness of the p...
متن کاملGabor Feature Based Face Recognition Using Supervised Locality Preserving Projection
This paper introduces a novel Gabor-based supervised locality preserving projection (GSLPP) method for face recognition. Locality preserving projection (LPP) is a recently proposed method for unsupervised linear dimensionality reduction. LPP seeks to preserve the local structure which is usually more significant than the global structure preserved by principal component analysis (PCA) and linea...
متن کاملApplication of Locality Preserving Projections in Face Recognition
Face recognition technology has evolved as an enchanting solution to address the contemporary needs in order to perform identification and verification of identity claims. By advancing the feature extraction methods and dimensionality reduction techniques in the application of pattern recognition, a number of face recognition systems has been developed with distinct degrees of success. Locality...
متن کاملPerformance analysis of Linear appearance based algorithms for Face Recognition
Analysing the face recognition rate of various current face recognition algorithms is absolutely critical in developing new robust algorithms. In his paper we propose performance analysis of Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Locality Preserving Projections (LPP) for face recognition. This analysis was carried out on various current PCA, LDA and LPP based...
متن کامل