  There are many Local texture features each very in way they implement and
each of the Algorithm trying improve the performance. An attempt is made in
this paper to represent a theoretically very simple and computationally
effective approach for face recognition. In our implementation the face image
is divided into 3x3 sub-regions from which the features are extracted using the
Local Binary Pattern (LBP) over a window, fuzzy membership function and at the
central pixel. The LBP features possess the texture discriminative property and
their computational cost is very low. By utilising the information from LBP,
membership function, and central pixel, the limitations of traditional LBP is
eliminated. The bench mark database like ORL and Sheffield Databases are used
for the evaluation of proposed features with SVM classifier. For the proposed
approach K-fold and ROC curves are obtained and results are compared.
