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Paper Title: Singular Value Decomposition Application in Image Compression and Face Recognition
Authors Name: Ashwini A. Patil , Prof. J.H.Patil , Prof. S.P.Patil
Unique Id: IJSDR1909016
Published In: Volume 4 Issue 9, September-2019
Abstract: This project has applied theory of linear algebra called “singular value decomposition(SVD)” to digital image processing. Two specific areas of digital image processing are investigated and tested. One is digital image compression, and other is face recognition. SVD method can transform matrix A into product 〖USV〗^T, which allows us to refactoring a digital image in three matrices. The using of singular values of such refactoring allows us to represent the image with a smaller set of values, which can preserve useful features of the original image, but use less storage space in the memory, and achieve the image compression process. The experiments with different singular value are performed, and the compression result was evaluated by compression ratio and quality measurement. To perform face recognition with SVD, we treated the set of known faces as vectors in a subspace, called “face space”, spanned by a small group of “base-faces”. The projection of a new image onto the base-face is then compared to the set of known faces to identify the face. All tests and experiments are carried out by using MATLAB as computing environment and programming language.
Keywords: Image processing, Image Compression, Face recognition, Singular value decomposition(SVD).
Cite Article: "Singular Value Decomposition Application in Image Compression and Face Recognition", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 9, page no.111 - 116, September-2019, Available :http://www.ijsdr.org/papers/IJSDR1909016.pdf
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Publication Details: Published Paper ID: IJSDR1909016
Registration ID:190951
Published In: Volume 4 Issue 9, September-2019
DOI (Digital Object Identifier):
Page No: 111 - 116
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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