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Journal ArticleDOI

Face recognition based on discriminant fractional Fourier feature extraction

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TLDR
This paper uses a two-dimensional separability judgment to select appropriate value of angle parameter for discrete fractional Fourier transform and presents a reformative Fisherface method to extract discriminative features from the preprocessed images and perform the classification using the nearest neighbor classifier.
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This article is published in Pattern Recognition Letters.The article was published on 2006-10-01. It has received 39 citations till now. The article focuses on the topics: Fractional Fourier transform & Fourier transform.

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Citations
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Journal ArticleDOI

WND-CHARM: Multi-purpose image classification using compound image transforms

TL;DR: A multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classification accuracy comparable to state-of-the-art task-specific image classifiers.
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Face and palmprint pixel level fusion and Kernel DCV-RBF classifier for small sample biometric recognition

TL;DR: The experimental results demonstrate that the proposed biometric fusion recognition approach is a rather effective solution for the small sample recognition problem.
Journal ArticleDOI

Feature extraction using Radon and wavelet transforms with application to face recognition

TL;DR: A new pattern recognition framework for face recognition based on the combination of Radon and wavelet transforms, which is invariant to variations in facial expression, and illumination, and robust to zero mean white noise is presented.
Journal ArticleDOI

Application of fractional Fourier transform for classification of power quality disturbances

TL;DR: In this article, the authors presented fractional Fourier transform (FRFT) based feature extraction as a new technique for classification of power quality disturbances (PQDs) for mitigation of PQDs.
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Locally linear reconstruction for instance-based learning

TL;DR: This paper proposed structured ways to set important model parameters, based on locally linear reconstruction (LLR), and employed sequential minimal optimization for solving quadratic programming step involved in LLR for classification to reduce the computational complexity.
References
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Journal ArticleDOI

Eigenfaces for recognition

TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
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Eigenfaces vs. Fisherfaces: recognition using class specific linear projection

TL;DR: A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.
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Statistical pattern recognition: a review

TL;DR: The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system and identify research topics and applications which are at the forefront of this exciting and challenging field.
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The FERET evaluation methodology for face-recognition algorithms

TL;DR: Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems.
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Statistical Pattern Recognition

TL;DR: In this paper, the primary goal of pattern recognition is supervised or unsupervised classification, and the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been used.
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