Face Recognition using LDA and Local MLP
نویسندگان
چکیده
منابع مشابه
Local Binary LDA for Face Recognition
Extracting discriminatory features from images is a crucial task for biometric recognition. For this reason, we have developed a new method for the extraction of features from images that we have called local binary linear discriminant analysis (LBLDA), which combines the good characteristics of both LDA and local feature extraction methods. We demonstrated that binarizing the feature vector ob...
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Face recognition from images is a sub-area of the general object recognition problem. It is of particular interest in a wide variety of applications. Here, the face recognition is based on the new proposed modified PCA algorithm by using some components of the LDA algorithm of the face recognition. The proposed algorithm is based on the measure of the principal components of the faces and also ...
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Article history: Received 28 January 2015 Accepted 25 February 2015 Available online 6 March 2015
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Facial feature extraction with enhanced discriminatory power plays an important role in face recognition (FR) applications. Linear discriminant analysis (LDA) is a powerful tool used for dimensionality reduction and feature extraction in FR tasks. However, the classification performance of traditional LDA is often degraded, due to two factors: 1) their classification accuracies suffer from the ...
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Low-dimensional feature representation with enhanced discriminatory power is of paramount importance to face recognition (FR) systems. Most of traditional linear discriminant analysis (LDA)-based methods suffer from the disadvantage that their optimality criteria are not directly related to the classification ability of the obtained feature representation. Moreover, their classification accurac...
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ژورنال
عنوان ژورنال: Journal of Korean Institute of Intelligent Systems
سال: 2006
ISSN: 1976-9172
DOI: 10.5391/jkiis.2006.16.3.367