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@article{153486,
        author = {ANUPAMA and Dr.Madhu.H.Gowda and Dr.Mamatha.C.M},
        title = {An effective model for Heterogeneous Face recognition in a static background},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {7},
        pages = {372-376},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=153486},
        abstract = {Real time faces images are captured in different spectral bands are referred to as heterogeneous. In this paper, the new approach based on low resolution heterogeneous face recognition and synthesis  is  proposed.  In  the  recognition  section, multi block local binary pattern (MBLBP) is used as facial representation for low resolution images. Then Canonical Correlation Analysis (CCA) is a applied to learn the mapping between the different LBP-face patterns. The corresponding matching scores are calculated in the CCA subspace for the final decision. In the synthesis section, according to the CCA transformation matrices obtained above, we apply ridge regression to determine an approximate linear relation between the target pattern image and the projection  vector  of  the  probe.  The  work shows  a practical solution for reliable heterogeneous face synthesis.},
        keywords = {Adaboost, DoG, Face Recognition, Heterogeneous, MB-LBP},
        month = {},
        }