Multiple Region Range Face Recognition Based on Fuzzy Integral Using Curvature Feature

The surface curvatures extracted from the face contain the most important personal facial information. In particular, the face shape using depth information in the face represents personal features in detail. In this paper, we develop a method for recognizing range face images by combining the multiple face regions, using Fisherface method, and fuzzy integral. For the proposed approach, the first step uses face curvatures that helps extract facial features for range face images, after normalization using the SVD. As a result of this process, we obtain curvature feature for each region range face. The second step of approach concerns the application of PCA and Fisherface method to each component range face. The reason for adapted PCA and Fisherface method is these can maintain the surface attribute for face curvature, even though these can generate the reduced image dimension. In the last step, the aggregation of the individual classifiers using the fuzzy integral is explained for each component. The experimental results obtain that the approach presented in this paper have outstanding classification in comparison to the results obtained by other methods.