Recognition of human front faces using knowledge-based feature extraction and neurofuzzy algorithm

Abstract A recognition method of human front faces using knowledge-based feature extraction and a neuro-fuzzy algorithm is proposed. In the preprocessing step we extract the face part from the homogeneous background by tracking face boundaries, where we assume that the face part is located in the center of a captured image. Then, based on a priori knowledge of human faces, we extract five normalized features. In the recognition step we propose a neuro-fuzzy algorithm that employs a trapezoidal fuzzy membership function and modified error backpropagation (EBP) algorithm. The former absorbs variation of feature values and the latter shows good learning efficiency. Computer simulation results with 80 test images of 20 persons show that the proposed neuro-fuzzy method yields higher recognition rate than the conventional ones.

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