International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 11, No. 7, 8 Jul. 2019
Cover page and Table of Contents: PDF (size: 675KB)
Face Recognition based Texture Analysis Methods
Full Text (PDF, 675KB), PP.1-8
Views: 0 Downloads: 0
Author(s)
Index Terms
Face recognition, LBP, GLCM, Euclidean distance, Cosine distance, Manhattan distance
Abstract
A unimodal biometric system based Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) is developed to recognize the facial of 40 subjects. The matching process is implemented using three classifiers: Euclidean distance, Manhattan distance, and Cosine distance. The maximum accuracy (100%) is satisfied when GLCM and LBP are applied with Euclidean distance. The accuracy result of these two methods is advanced the Principle Component Analysis (PCA) and Fourier Descriptors (FDs) recognition rate. The ORL database is considered for constructing the proposed biometric system.
Cite This Paper
Marwa Y. Mohammed, "Face Recognition based Texture Analysis Methods", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.7, pp. 1-8, 2019. DOI: 10.5815/ijigsp.2019.07.01
Reference
[1]Sarah BENZIANE, Abdelkader BENYETTOU, "An introduction to Biometrics ", (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 4, 2011.
[2]Marcos Faundez-Zanuy, "Biometric security technology", IEEE Aerospace and Electronic Systems Magazine, Vol.21 No. 6, pp. 15-26, June 2006.
[3]Ramadan Gad, Ayman El-Sayed, Nawal El-Fishawy, M. Zorkany, "Multi-Biometric Systems: A State of the Art Survey and Research Directions", International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 6, No. 6, 2015
[4]Anil K. Jain, Arun Ross, Salil Prabhakar, "An Introduction to Biometric Recognition ", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 1, January 2004.
[5]H. Proenca, "Towards Non-Cooperative Biometric Iris Recognition", Ph.D Thesis, University of Beira Interior, October 2006.
[6]Prachi Agarwal, Naveen Prakash, "Modular Approach for Face Recognition System using Multilevel Haar Wavelet Transform, Improved PCA and Enhanced Back Propagation Neural Network ", International Journal of Computer Applications, Vol. 75, No.7, August 2013.
[7]Urvashi Bakshi, Rohit Singhal, "A New Approach of Face Recognition Using DCT, PCA, And Neural Network in Matlab", International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Vol. 3, Issue 3, 2014.
[8]Dan Zou, Hong Zhang, "Face Recognition Method Based On 2DLDA And SVM Optimated By PSO Algorithm ", Advances in Intelligent Systems Research, Vol. 130, 2016.
[9]R.Kavitha, V.Nisha, "Analysis Of Face Recognition Using Support Vector Machine", International Conference on Emerging trends in Engineering, Science and Sustainable Technology (ICETSST), 2017
[10]Muthana H. Hamd, Marwa Y. Mohammed, " Multimodal Biometric System Based Face-Iris Feature Level Fusion", International Journal Modern Education and Computer Science (IJMECS), Vol. 11, No. 5, 2019
[11]S. Marcel, Y. Rodriguez, G. Heusch, "On the Recent Use of Local Binary Patterns for Face Authentication", International Journal Of Image And Video Processing, Special Issue On Facial Image Processing, May 2007.
[12]Md. Abdur Rahim, Md. Najmul Hossain, Tanzillah Wahid, Md. Shafiul Azam, "Face Recognition using Local Binary Patterns (LBP)", Global Journal of Computer Science and Technology Graphics & Vision, Vol.13, Issue 4, 2013.
[13]Redouan Korchiynel, Sidi Mohamed Farssi, Abderrahmane Sbihi, Rajaa Touahni, Mustapha Tahiri Alaoui, "A Combined Method of Fractal and GLCM Features for MRI and CT Scan Images Classification", Signal & Image Processing : An International Journal (SIPIJ), Vol.5, No.4, August 2014
[14]Emrullah ACAR, "Extraction of Texture Features from Local Iris Areas by GLCM and Iris Recognition System Based on KNN", European Journal of Technic, Vol. 6, No.1, 2016.
[15]Girisha A. B., M. C. Chandrashekhar, M. Z. Kurian, "Texture Feature Extraction of Video Frames Using GLCM", International Journal of Engineering Trends and Technology (IJETT), Vol. 4, Issue 6, June 2013