@article{MAKHILLAJIT20141335812,
    title = {Recognition of Face Images Through the Fusion Approach},
    journal = {Asian Journal of Information Technology},
    volume = {13},
    number = {3},
    pages = {150-155},
    year = {2014},
    issn = {1682-3915},
    doi = {ajit.2014.150.155},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2014.150.155},
    author = {V. and},
    keywords = {Color face recognition,color local texture features,combination,principal component analysis,linear discriminant analysis},
    abstract = {Face Recognition System should be able to automatically detect 
  a face in images. This involves extraction of its features and then recognizes 
  it, regardless of lighting, ageing, occlusion, expression, illumination and 
  pose. Color local texture method do not easy to recognize the face and if variation 
  in face means do not get proper results. Linear Discriminant Analysis (LDA) 
  is commonly used technique for data classification and dimensionality reduction. 
  LDA approach overcomes the above problem. The objective of LDA is to perform 
  dimensionality reduction while preserving as much of the class discriminatory 
  information as possible. Linear discriminant analysis is also known as Fisher’s 
  discriminant analysis and it searches for those vectors in the underlying space 
  that best discriminate among classes.}
    }