( Online- ISSN 2454 -3195 ) New DOI : 10.32804/RJSET

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Vol -  8, Issue- 1 ,         Page(s) : 23 - 26  (2018 ) DOI :


Face recognition is one of the most crucial component in computer vision and human interaction. Our project’s main concern is to mark attendance using face recognition with highest efficiency. Face recognition system consist of principal component analysis(PCA)[3] which is used to reduce the dimension of an image by feature extraction on the basis of illumination, intensity of particular region of common behavior identify in particular object. The algorithm calculate eigen value and eigenvector from covariance matrix of a training image set. The most variant data to a particular region is known as first principal component and component orthogonal to first principal component is known as second principal component. Face recognition is done by using support vector machine algorithm[1]. the input data as an image is matched with our application database and matched information will circulate to relative mentor .Haar cascade classifier is used to classify the various component of the images . The eye blinking motion will be detected to ensuring about real face not an face from any photograph.

  1. Corinna cortes, Vladimir vapnik “Support vector machine”, Kluwer academic publisers, Boston, vol-20, 1995
  2. Liton Chandra Paul, Abdulla Al Sumam, “Face Recognition Using Principal Component Analysis Method”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 1, Issue 9, November 2012
  3. Navin Prakash, Dr.Yashpal Singh, “Support Vector Machines for Face Recognition”, International Research Journal of Engineering and Technology (IRJET), Volume: 02 Issue: 08 | Nov-2015
  4. Yassin M. Y. Hasan and Lina J. Karam, “Morphological Text Extraction from Images”,IEEE Transactions On Image Processing, vol. 9, No. 11, 2000
  5. Eftychios A. Pnevmatikakis, Petros Maragos “An Inpainting System For Automatic Image Structure-Texture Restoration With Text Removal”, IEEE trans. 978-1-4244-1764,  2008 
  6. Aria Pezeshk and Richard L. Tutwiler, “Automatic Feature Extraction and Text Recognition from Scanned Topographic Maps”, IEEE Transactions on geosciences and remote sensing, VOL. 49, NO. 12,  2011
  7. Xiaoqing Liu and Jagath Samarabandu, “Multiscale Edge-Based Text Extraction From Complex Images”, IEEE Trans., 1424403677, 2006 
  8. Nobuo Ezaki, Marius Bulacu Lambert , Schomaker , “Text Detection from Natural Scene Images: Towards a System for Visually Impaired Persons” , Proc. of 17th Int. Conf. on Pattern Recognition (ICPR), IEEE Computer Society, pp. 683-686, vol. II, 2004
  9. Uday Modha, Preeti Dave, “ Image Inpainting-Automatic Detection and Removal of Text From Images”, International Journal of Engineering Research and Applications (IJERA),  ISSN: 2248-9622 Vol. 2, Issue 2, 2012

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