Pose Invariant Face Recognition using Neuro-Fuzzy Approach

In this paper a pose invariant face recognition using neuro-fuzzy approach is proposed. Here adaptive neuro fuzzy interface system (ANFIS) classifier is used as neuro-fuzzy approach for pose invariant face recognition. In the proposed approach the preprocessing of image is done by using adaptive median filter. It removes the salt pepper noise from the original images. From these denoised images features are extracted. Here Principal component analysis (PCA) is used for extracting the features of an image under test. Then ANFIS classifier is used for face recognition. PCA calculate the principal components and are used by ANFIS for further process. Here in this paper combination of PCA and ANFIS is represented as PCA+ANFIS. In the paper standard ORL face database is used for experimental results. The performance PCA+ANFIS with LDA+ANFIS and ICA+ANFIS is analyzed and compared. From experimental results it is shown that PCA+ANFIS outperforms than other two approaches. PCA+ANFIS is also compared by existing feed forward neural network (FFBNN) approach. The results show that proposed approach gives better outputs in terms of accuracy, sensitivity and specificity.