A novel efficient and robust methodology for quick face recognition by using Fuzzy Rule based Local Binary Pattern (FRLBP) has been presented. The face image is said to be divided into a number of 3x3 regions, called as micro patterns, indicating the structure of the gray level pixels within a neighborhood to describe the spatial context of the image to reduce the impact of gray level uncertainty representation of images. The gray level pixel is represented as fuzzy number to evaluate the membership degree of the central pixel to the others within a neighborhood. A Local texture distributor for each of the 3x3 neighborhood, called LBP descriptor, is obtained by applying fuzzy Rules from which the FRLBP feature distributions are extracted. Use of fuzzy contributes to more than a single bin in the distribution of LBP values in the feature vector. The recognition is performed using a nearest neighbor classifier in the computed feature space with Chi square as a dissimilarity measure. Experiments clearly show that the use of FRLBP leads to improved reliable face recognition than to the original methods, LBP and Rule Based LBP.