Open Access Open Access  Restricted Access Subscription or Fee Access

An Innovative Study on PCA and ICA Based Face Recognition System for Static Images Using Interval Type2 Fuzzy Logic

Tarun Dhar Diwan, Rohit Miri, Pramod Rajput

Abstract


Within the last several years, Recognition of Human's Facial Expression has been very active research area of computer vision. It has the important role in the human-computer interaction (HCI) systems. This paper proposes a novel interval type2 fuzzy method for facial expression recognition on still images of the face. The new technique involves in extracting mathematical data from some special regions of the face and fed them to an interval type2 fuzzy rule-based system. Fuzzy fictions operation uses trapezoidal membership functions for both input and output. The Distinct feature of a system is its simplicity and high accuracy. Experimental results on database indicate good performance of the developed technique. New approach of information extraction based on interval type2 fuzzy logic, which can be used for robust face recognition system is proposed here. The results clearly confirmed the superiority of proposed approach. To improve the face recognition performance, a PCA-ICA signal preprocessing and interval type2 fuzzy based recognition algorithm is proposed. In this approach, signals of human face are firstly preprocessed effectively by combination of Principal Component Analysis (PCA) and Independent Component Analysis (ICA), and then processed with interval type2 fuzzy logic for the purpose of face recognition.

Keywords


Face Recognition System, Principle Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminate Analysis (LDA), Interval Type-2 Fuzzy Inference System, Interval Type-2 Fuzzy Logic.

Full Text:

PDF

References


Smith R. S., T. Windeatt, “ Facial Expression Detection using Filtered Local Binary Pattern Features with ECOC Classifiers and Platt

Shafiq M. Z., A. Khanum,“ A „personalized facial expression recognition system using case based reasoning,“ 2nd IEEE International Conference on Emerging Technologies, Peshawar, pp. 630-635, 2006.

Raouzaiou A., S. Ioannou, K. Karpouzis, N. Tsapatsoulis, S. Kollias, R. Cowie ,“An Intelligent Scheme for Facial Expression Recognition, “Artificial Neural Networks and Neural Information Processing, Lecture notes in Computer Science 2714, Springer, pp. 1109 ,1116, 2003.

Friesen W., P. Ekman, “Emotional facial action coding system“, unpublished manual, 1984.

Liu J.Q., Q. Zhen Fan, “Research of feature extraction method on Facial Expression change, “Advanced Materials Research Volumes 211 – 212, 2011.

Xiang T., M.K.H. Leung, and S.Y. Cho, “Expression recognition using fuzzy patio-temporal modeling, “Pattern Recognition, vol. 41, pp. 204-216, 2008.

Jamshidnezhad A., “A Learning Fuzzy Model for Emotion Recognition, “European Journal of Scientific Research ISSN 1450-216X Vol.57 No.2, pp.206-211, 2011.

Usman Akram M., Irfan Zafar, Wasim Siddique Khan and Zohaib Mushtaq “Facial Expression Recognition Based On Fuzzy Logic“ International Conference on Computer Vision Theory and Applications, P.383-388, 2008.

Dongcheng S., J. Jieqing , “The method of facial expression recognition based on DWT-PCA/LDA, “ International congress on Image and Signal Processing (CISP), Volume: 4, pp. 1970 – 1974, 2010.

Vishwakarma V. P., S. Pandey, and M. N. Gupta “Fuzzy based Pixel wise Information Extraction for Face Recognition,“ IACSIT International Journal of Engineering and Technology Vol. 2, No.1, ISSN: 1793-8236, February, 2010.

Li S. Z. and A. K. Jain, Handbook of Face Recognition, Springer, 2005.

Delac K, M. Grgic and S. Grgic, “Independent Comparative Study of PCA, ICA, and LDA on the FERET Data Set,” International Journal of Imaging Systems and Technology, vol. 15, issue 5, pp. 252-260, 2005.

Kwak K. C. and W. Pedrycz, “Face recognition using a fuzzy fisher face classifier,” Pattern Recognition, vol. 38, pp. 1717-1732, 2005.

Yang W., H. Yan, J. Wang and J. Yang, “Face recognition using complete Fuzzy LDA,” Face recognition using Complete Fuzzy LDA,” in Proc. 19th Int. Conf. on Pattern Recognition 2008, pp. 1-4, Dec. 2008.


Refbacks

  • There are currently no refbacks.