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Infrared Image Face Recognition Using Random Projection and Sparse Representation

Author: LiuBin
Tutor: LiangJiMin
School: Xi'an University of Electronic Science and Technology
Course: Circuits and Systems
Keywords: Face Recognition Visible light Far-infrared light Random projection Sparse Representation
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 348
Quote: 4
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The face recognition technology has made ??great achievements , but also faces many unresolved problems , the visible light image performance of face recognition system is susceptible to the influence of illumination changes is one of the problems . Thermal infrared images from the illumination changes applied to face recognition can achieve good results . However, due to thermal infrared can not penetrate the glass , if the pending identify a person wearing glasses , the image rendering sunglasses form , will cause a sharp decline of recognition performance . In this paper, the thermal infrared face recognition system glasses cover research to characterize the robustness of classification and recognition method based on random projection and sparse . First map the original high-dimensional image data using random projection to low-dimensional subspace of transformation , to achieve the purpose of data dimensionality reduction . Then using the test sample with a very small number of training samples linear classification and recognition method based on Sparse Representation effective isolation cover noise . For the reconstruction of the test sample is estimated based on various types of characterization factor , this paper proposes the Criterion two classifications are reconstructed the residuals and characterization coefficient effectiveness accumulated factor . The same time , in order to achieve great robustness veiled take images horizontal quartered strategy , random projection and sparse characterization in each decile block respectively , four average criterion value for classification . The database used in this experiment for American the Equinox companies collect and record the visible and far infrared face image database , selected according to need 44 people both wear glasses also do not wear glasses far infrared light and its every frame corresponding to the visible light face image . The CSU face recognition using improved evaluation system of the proposed method with the appearance - based face recognition method , principal component analysis , linear discriminant analysis and Bayesian method , comparative assessment based on the far-infrared and visible light images . The assessment results show that this method can effectively solve the problems of the glasses cover the impact of thermal infrared face image recognition rate , and its recognition performance is better than the principal component analysis , linear discriminant analysis , as well as the Bayesian method .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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