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International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.10, No.3, Mar. 2018

Multi Featured Fuzzy based Block Weight Assignment and Block Frequency Map Model for Transformation Invariant Facial Recognition

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Author(s)

Kapil Juneja, Chhavi Rana

Index Terms

Transformation Invariant;Misaligned;Rotational;Structural;Block Featured

Abstract

Misalignment of the camera, some jerk during capture is natural that results some tilt or geometric transformed photo. The accurate recognition on these misaligned facial images is one of the biggest challenges in real time systems. In this paper, a fuzzy enabled multi-parameter based model is presented, which is applied to individual blocks to assign block weights. At first, the model has divided the image into square segments of fixed size. Each segmented division is analyzed under directional, structural and texture features. Fuzzy rule is applied on the obtained quantized values for each segment and to assign weights to each segment. While performing the recognition process, each weighted block is compared with all weighted-feature blocks of training set. A weight-ratio to exactly map and one-to-all map methods are assigned to identify overall matching accuracy. The work is applied on FERET and LFW datasets with rotational, translational and skewed transformation. The comparative observations are taken against KPCA and ICA methods. The proportionate transformation specific observations show that the model has improved the accuracy up to 30% for rotational and skewed transformation and in case of translation the improvement is up to 11%.

Cite This Paper

Kapil Juneja, Chhavi Rana," Multi Featured Fuzzy based Block Weight Assignment and Block Frequency Map Model for Transformation Invariant Facial Recognition", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.10, No.3, pp. 1-8, 2018.DOI: 10.5815/ijigsp.2018.03.01

Reference

[1]Xiaohua Xie, Jianhuang Lai, and Wei-Shi Zheng, "Extraction of illumination invariant facial features from a single image using nonsubs ampled contourlet transform", Pattern Recognition, Vol 43, pp 4177-4189, 2010

[2]Saeid. Fazli, and Leila and Ali Heidarloo, "Wavelet Based Age Invariant Face Recognition using Gradient Orientation", International Conference on Advances in Computer and Electrical Engineering, pp 13-16, 2012

[3]Amany Farag and Randa Atta, "Illumination Invariant Face Recognition Using the Statistical Features of BDIP and Wavelet Transform", International Journal of Machine Learning and Computing, Vol 2, Issue 1, 2012

[4]Weihong Deng, Jiani Hu, Jiwen Lu and Jun Guo, "Transform-Invariant PCA: A Unified Approach to Fully Automatic Face Alignment, Representation, and Recognition", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, Vol 36, Issue 6, pp 1275-1284, 2014

[5]Shubhankar De and Ranjan Parekh, "Illumination and Expression Invariant Automatic Human Face Recognition using Wavelet, Eigen and Fisher Analysis", International Journal of Computer Applications, Vol 117, Issue 21, 2015

[6]R.Pavithra, A. Usha Ruby, J. George and Chellin Chandran, "Scale Invariant Feature Transform Based Face Recognition from a Single Sample per Person", International Journal of Computational Engineering Research, Vol 4, Issue 10, pp 41-47, 2014

[7]Aman Kumar, Aditya Vardhan Srivastava and Pavan Singh Yadav, "Survey on Age Invariant Facial Recognition", Advances in Computer Science and Information Technology, Vol 2, Issue 5, pp 450-453, 2015

[8]Jeet Kumar, Aditya Nigam, Surya Prakash and Phalguni Gupta, "An Efficient Pose Invariant Face Recognition System", Proceedings of the International Conference on Soft Computing for Problem Solving, Vol 2, pp 145-152, 2012

[9]Haresh D., Chande and Zankhana H. Shah, "Illumination Invariant Face Recognition System",  International Journal of Computer Science and Information Technologies, Vol 3, Issue 3, pp 4010-4014, 2012

[10]Surya Kant Tyagi and Pritee Khanna, "Face Recognition Using Discrete Cosine Transform and Nearest Neighbor Discriminant Analysis",  International Journal ofEngineering and Technology, Vol 4, Issue 3, 311-314, 2012

[11]Felix Juefei-Xu, Khoa Luu, Marios Savvides, Tien D. Bui, and Ching Y. Suen, "Investigating Age Invariant Face Recognition Based on Periocular Biometrics",  International Joint Conference on Biometrics, pp 1-7, 2011

[12]Hardeep Kaur and Amandeep Kaur, "Illumination Invariant Face Recognition", International Journal of Computer Applications. Vol 64, Issue 21, pp 23-27, 2013

[13]Anissa Bouzalmat, Arsalane Zarghili and Jamal Kharroubi, "Facial Face Recognition Method using Fourier Transform Filters Gabor and R_LDA", International Conference on Intelligent Systems and Data Processing, pp 18-24, 2011

[14]Hadis Mohseni Takallou and Shohreh Kasaei, "Head pose estimation and face recognition using a nonlinear tensor-based model", IET Computer Vision, Vol 8, Issue 1, pp 54-65, 2014

[15]Hadis Mohseni Takallou and Shohreh Kasaei, "Multiview face recognition based on multilinear decomposition and pose manifold", IET Image Processing, Vol 8, Issue 5, pp 300-309, 2014

[16]Wonjun Kim, Sungjoo Suh, Wonjun Hwang and Jae-Joon Han, "SVD Face: Illumination-Invariant Face Representation", IEEE SIGNAL PROCESSING LETTERS, Vol 21, Issue 11, pp 1336-1340, 2014

[17]Mohammad Reza Faraji and Xiaojun Qi, "Face Recognition under Varying Illumination with Logarithmic Fractal Analysis", IEEE SIGNAL PROCESSING LETTERS, Vol 21, Issue 12, pp 1457-1461, 2014

[18]Gaurav Goswami, Mayank Vatsa and Richa Singh, "RGB-D Face Recognition With Texture and Attribute Features", IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, Vol 9, Issue 10, pp 1629-1640, 2014

[19]Ali. Javed, "Face recognition based on principal component analysis." International Journal of Image, Graphics and Signal Processing, Vol 5, Issue, 2, (2013): pp 38-44.

[20]Subrat Kumar Rath, Siddharth Swarup Rautaray, "A Survey on Face Detection and Recognition Techniques in Different Application Domain." International Journal of Modern Education and Computer Science, Vol 6, Issue 8 (2014): pp 34-44.

[21]K. Srinivasa Reddy, V. Vijaya Kumar, B. Eswara Reddy. "Face recognition based on texture features using local ternary patterns." International Journal of Image, Graphics and Signal Processing Vol 7, Issue 10, (2015): pp 37-46.

[22]Narpat A. Singh, Manoj B. Kumar, Manju C. Bala. "Face Recognition System based on SURF and LDA Technique." International Journal of Intelligent Systems and Applications Vol 8, Issue 2,  (2016): pp 13-19.

[23]Tripti Goel, Vijay Nehra, Virendra P. Vishwakarma. "Pose Normalization based on Kernel ELM Regression for Face Recognition." International Journal of Image, Graphics & Signal Processing Vol 9, Issue 5. (2017), pp 68-75

[24]Kapil Juneja, "MPMFFT based DCA-DBT integrated probabilistic model for face expression classification." Journal of King Saud University-Computer and Information Sciences (2017).

[25]Kapil Juneja, "Multiple feature descriptors based model for individual identification in group photos." Journal of King Saud University-Computer and Information Sciences (2017).

[26]Kapil Juneja, "MFAST Processing Model for Occlusion and Illumination Invariant Facial Recognition." Advanced Computing and Communication Technologies. Springer Singapore, 2016. 161-170.

[27]Kapil Juneja, "Ring Segmented and Block Analysis Based Multi-feature Evaluation Model for Contrast Balancing." International Conference on Information, Communication and Computing Technology. Springer, Singapore, 2017

[28]Kapil Juneja, and Nasib Singh Gill. "Tied multi-rubber band model for camera distance, shape and head movement robust facial recognition." Applied and Theoretical Computing and Communication Technology (iCATccT), 2015 International Conference on. IEEE, 2015.

[29]Kapil Juneja, and Nasib Singh Gill. "A hybrid mathematical model for face localization over multi-person images and videos." Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions), 2015 4th International Conference on. IEEE, 2015.

[30]Weihong Deng, Jiani Hu, Zhongjun Wu, Jun Guo, Lighting-aware face frontalization for unconstrained face recognition, Pattern Recognition, Volume 68, 2017, Pages 260-271

[31]Hemprasad Y. Patil, Ashwin G. Kothari, Kishor M. Bhurchandi, Expression invariant face recognition using local binary patterns and contourlet transform, Optik - International Journal for Light and Electron Optics, Volume 127, Issue 5,2016, Pages 2670-2678

[32]Mohd. Abdul Muqeet, Raghunath S. Holambe, Local binary patterns based on directional wavelet transform for expression and pose-invariant face recognition, Applied Computing and Informatics, 2017