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Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP
Sujatha B M , K Suresh Babu, K B Raja, Venugopal K R
Pages - 283 - 303     |    Revised - 30-09-2015     |    Published - 31-10-2015
Volume - 9   Issue - 5    |    Publication Date - September / October 2015  Table of Contents
Biometrics, CLBP, DWT, Face Recognition, FFT, Histogram.
The characteristics of human body parts and behaviour are measured with biometrics, which are used to authenticate a person. In this paper, we propose Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP. The face images are preprocessed to enhance sharpness of images using Discrete Wavelet Transform (DWT) and Laplacian filter. The Compound Local Binary Pattern (CLBP) is applied on sharpened preprocessed face image to compute magnitude and sign components. The histogram is applied on CLBP components to compress number of features. The Fast Fourier Transformation (FFT) is applied on preprocessed image and compute magnitudes. The histogram features and FFT magnitude features are fused to generate final feature. The Euclidian Distance (ED) is used to compare final features of test face images with data base face images to compute performance parameters. It is observed that the percentage recognition rate is high in the case of proposed algorithm compared to existing algorithms.
CITED BY (1)  
1 Thamizharasi, A., & Jayasudha, J. S. (2016). An Illumination Invariant Face Recognition by Selection of DCT Coefficients. International Journal of Image Processing (IJIP), 10(1), 14.
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 Faisal R. AI-Osaimi, Mohammed Bennamoun and Ajmal Main, “Spatially optimized Data- Level Fusion of Texture and Shape for Face Recognition,” IEEE Transactions on Image Processing, Vol. 21, No.2, pp 859 -872 ,2012.
2 Raghuraman Gopalan, Simha Taheri, Pavan Turaga, Rama Challappa, “A Blur-Robust Descriptor with Applications to Face Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 34, No 6, pp.1220-1226, 2012.
3 Ping-Han Lee, Szu-Wei Wu and Yi-Ping Hung “Illumination Compensation using Oriented Local Histogram Equalization and Its Application to Face Recognition,” IEEE Transactions on Image processing, Vol 21, No 9, pp. 4280-4289, 2012.
4 Timo Ahonen, Abdenour Hadid and Matti Pietikainen, “Face Description with Local Binary Patterns: Application to Face Recognition,” IEEE Transactions on pattern analysis and Machine intelligence, Vol 28, No. 12, pp. 2037-2041, 2006.
5 Parama Bagchi, Debotosh Bhattacharjee and Mita Nasipuri “ Robust 3D Recognition in Presence of Pose and Partial Occlusiions or Missing Parts,” International Journal in Foundations of Computer Science and Technology, Vol. 4, No.4, pp. 21-35, 2014.
6 Michel F. Valstar and Maja Pantic, “Fully Automatic Recognition of the Temporal Phases of Facial Actions,” IEEE Transactions on systems, Man, and Cybernetics-Part B: Cybernetics, Vol-42, No. 1, pp. 28-42, 2012.
7 Wilman W.W. Zou, and Pong C.Yuen “Very Low Resolution Face Recognition Problem,” IEEE Transactions on Image Processing, Vol. 21, No. 1, pp.327-340, 2012.
8 Hu Han, Charles Otto, Xiaoming Liu and Anil K. Jain, “Demographic Estimation from Face Images: Human Vs. Machine Performance,” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.1-14, 2014.
9 Changxing Ding, Chang Xu and Dacheng Tao “Multi-Task Pose-Invariant Face Recognition,” IEEE Transactionson Image Processing, Vol. 24, No. 3, pp. 980-992, 2015.
10 Faisal Ahmed, Emam Hossain, A.S.M. Hossain Bari and ASM Shihavuddin, “Compound Local Binary Pattern (CLBP) for Robust Facial Expression Recognition,” IEEE International Symposium on Computational Intelligence and Informatics, pp.391-395, Budapest, Hungary, 2011.
11 Jae Young Choi, Yong Man Ro and Konstantinos N. Plataniotis “Color Local Texture Features for Color Face Recognition” IEEE Transactions on Image Processing, Vol. 21, No. 3, pp.1366-1380, 2012.
12 Jaffe Database, http://www.kasrl.org/jaffe_download.html.
13 ORL database, http://www.camrol.co.uk
14 Indian Face Database, http://viswww.cs.umass.edu/~vidit/Indian Face Database
15 J. Petrova, E. Ho·s·talkova, “Edge Detection in Medical Images using the Wavelet Transform,” Department of Computing and Control Engineering, Institute of Chemical Technology, Prague, Technicka 6, 16628 Prague 6, Czech Republic, 2011.
16 2-D-DWT,http://cnx.org/contents/a53d13be-b4f1-47c7-a783-dc965f5e945d@4/The-2-DDWT
17 [17] Madhulakshmi, Abdul Wahid Ansari, “Face Recognition Using Featured Histogram,” International Journal of Emerging Technology and Advanced Engineering Vol 3, Issue 8, pp.142- 147, 2013.
18 http://www.gamasutra.com/view/feature/132385/sponsored_feature_implementation.php
19 Pallavi D.Wadkar and MeghaWankhade, “Face Recognition using Discrete Wavelet Transforms,” International Journal of AdvancedEngineering Technology, vol. 3, pp. 239-242, 2012.
20 Swarup Kumar Dandapat and Sukadev Meher, “Performance Improvement for Face Recognition using PCA and Two-Dimensional PCA,” IEEE International Conference on Computer Communication and Informatics, pp. 1-5, 2013.
21 D Murugan, S Arumugam, K Rajalakshmi and Manish T, “Performance Evaluation of Face Recognition using Gabor Filter, Log Gabor filter and Discrete Wavelet Transform,” International Journal of computer science and Information Technology, vol. 2, no. 1, pp. 125133, 2010.
Associate Professor Sujatha B M
Acharya Institute of Technology - India
Dr. K Suresh Babu
Dept. of ECE, University Visvesvaraya College of Engineering, Bangalore, India. - India
Dr. K B Raja
Dept. of ECE, University Visvesvaraya College of Engineering, Bangalore, India. - India
Dr. Venugopal K R
University Visvesvaraya College of Engineering Bangalore, India. - India