Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/999
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dc.contributor.authorSolanki, Dhavalsinh-
dc.contributor.authorKothari, Ashish-
dc.date.accessioned2023-05-18T02:36:36Z-
dc.date.available2023-05-18T02:36:36Z-
dc.date.issued2015-
dc.identifier.citationSolanki, D. ,Kothari, A.(2015). Comparative Survey of Face Recognition Techniques. International Journal of Advance Engineering and Research Development (IJAERD), National Conference on Emerging Trends in Computer, Electrical & Electronics (ETCEE-2015), Vol. 2 No. 14, e-ISSN: 2348 - 4470 , print-ISSN:2348-6406,Impact Factor:3.134. http://ijaerd.com/index.php/IJAERD/article/view/5789en_US
dc.identifier.issn2348 - 4470-
dc.identifier.urihttp://10.9.150.37:8080/dspace//handle/atmiyauni/999-
dc.description.abstractFace recognition has been a fast emergent and exciting area in real time applications. Automatic face recognition has shown great achievement for high-quality images under embarrassed conditions. In this paper techniques of Face detection along with Face Recognition are discussed. Human and object frames, background frames are separated by implementing a face detection algorithms like Viola-Jones & Skin Detection algorithms. In this paper we have discussed, analyzed, & compare some popular face detection methods like PCA, LDA, PCA + LDA Hybridization and Gabor wavelet transformations and also tried to attempt a comparative study of these methods.en_US
dc.language.isoenen_US
dc.subjectPrincipal Component Analysis (PCA)en_US
dc.subjectViola- Jonesen_US
dc.subjectGabor Filtersen_US
dc.subjectFisher’s Linear Discriminant Analysis (FLDA)en_US
dc.titleComparative Survey of Face Recognition Techniquesen_US
dc.typeArticleen_US
Appears in Collections:01. Journal Articles

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