Journal ArticleDOI
Algebraic feature extraction for image recognition based on an optimal discriminant criterion
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TLDR
An important conclusion about the present method is that the Foley-Sammon optimal set of discriminant vectors is a special case of the set of optimal discriminant projection vectors.About:
This article is published in Pattern Recognition.The article was published on 1993-06-01. It has received 183 citations till now. The article focuses on the topics: Optimal discriminant analysis & Kernel Fisher discriminant analysis.read more
Citations
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Journal ArticleDOI
Two-dimensional PCA: a new approach to appearance-based face representation and recognition
TL;DR: A new technique coined two-dimensional principal component analysis (2DPCA) is developed for image representation that is based on 2D image matrices rather than 1D vectors so the image matrix does not need to be transformed into a vector prior to feature extraction.
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A new LDA-based face recognition system which can solve the small sample size problem
TL;DR: It is proved that the most expressive vectors derived in the null space of the within-class scatter matrix using principal component analysis (PCA) are equal to the optimal discriminant vectorsderived in the original space using LDA.
Journal ArticleDOI
2D-LDA: A statistical linear discriminant analysis for image matrix
Ming Li,Baozong Yuan +1 more
TL;DR: An innovative algorithm named 2D-LDA is proposed, which directly extracts the proper features from image matrices based on Fisher's Linear Discriminant Analysis, and achieves the best performance.
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Fisherpalms based palmprint recognition
TL;DR: The experimental results show that, in the proposed method, the palmprint images with resolution 32 × 32 are optimal for medium security biometric systems while those with resolution 64 × 64 are optimalFor high security biometrics systems.
Journal ArticleDOI
Multilinear Discriminant Analysis for Face Recognition
TL;DR: This paper presents a novel approach to solve the supervised dimensionality reduction problem by encoding an image object as a general tensor of second or even higher order, and proposes a discriminant tensor criterion, whereby multiple interrelated lower dimensional discriminative subspaces are derived for feature extraction.
References
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Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
Book
Fundamentals of digital image processing
TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
Journal ArticleDOI
Visual pattern recognition by moment invariants
TL;DR: It is shown that recognition of geometrical patterns and alphabetical characters independently of position, size and orientation can be accomplished and it is indicated that generalization is possible to include invariance with parallel projection.
Journal ArticleDOI
Low-dimensional procedure for the characterization of human faces
Lawrence Sirovich,Michael Kirby +1 more
TL;DR: In this article, a method for the representation of (pictures of) faces is presented, which results in the characterization of a face, to within an error bound, by a relatively low-dimensional vector.