In this paper, quaternion based fuzzy neural network classifier is proposed for MPIK dataset's view-invariant color face image recognition.
In the evaluation experiment, T=180 MPIK persons' faces are used to train the system during the enrollment stage.
For the recognition accuracy, a total of 10,000 randomly selected and repeated MPIK color face images with mixing up the trained T=180 persons' faces plus 20 more persons' faces excluded from the training database sets are tested.
To evaluate the effectiveness of the hypercomplex Gabor filter proposed by  for feature extraction used in this comparative study, the hypercomplex Gabor filter is operated on all the MPIK RGB dataset color face images as in section 5.1.
In terms of recognition accuracy, the proposed quaternion based fuzzy neural network outperform hypercomplex Gabor filter, conventional NMF and BDNMF in recognizing view-invariant, noise influenced and scale invariant MPIK color face images.