Abstract:

For the problem that the grain feature extracted by the traditional LBP operator is not complete and cannot fully represent the local feature of face, an improved LBP operator was proposed based on neighborhood correlation. The operator first calculated the neighborhood correlation of each pixel within the window. And then a new NC_LBP operator was constructed by the neighborhood correlation mean and variance; furthermore, the image local histogram feature was extracted as the basis for face recognition; finally, the Chi square statistic method was used to calculate the histogram dissimilarity, and the classification was performed with KNN algorithm. Simulation results show that the proposed improved NC_LBP operator has achieved good recognition results in the ORL, JAFFE and YALE face databases, and the discrimination of features is obvious. The recognition accuracy is greatly improved.

Key words: face recognition, neighborhood correlation, LBP operator