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Proceedings Paper

Face recognition using transform domain texture features
Author(s): Rangaswamy Y.; Ramya S K; K B Raja; Venugopal K. R.; L. M. Patnaik
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Paper Abstract

The face recognition is an efficient biometric system to identify a person. In this paper, we propose Face Recognition using Transform Domain Texture Features (FRTDTF). The face images are preprocessed and two sets of texture features are extracted. In first feature set, the Discrete Wavelet Transform (DWT) is applied on face image and considered only high frequency sub band coefficients to extract edge information efficiently. The Dual Tree Complex Wavelet Transform (DTCWT) is applied on high frequency sub bands of DWT to derive Low and High frequency DTCWT coefficients. The texture features of DTCWT coefficients are computed using Overlapping Local Binary Pattern (OLBP) to generate feature set 1. In second feature set, the DTCWT is applied on preprocessed face image and considered all frequency sub bands coefficients to extract significant information and edge information of face image. The texture features of DTCWT matrix are computed using OLBP to generate feature set 2. The final feature set is the concatenation of feature set 1 and set 2. The Euclidian distance (ED) is used to compare test image features with features of face images in the database. It is observed that, the performance parameter values are better in the case of proposed algorithm compared to existing algorithms.

Paper Details

Date Published: 24 December 2013
PDF: 5 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90671P (24 December 2013); doi: 10.1117/12.2051957
Show Author Affiliations
Rangaswamy Y., Alpha College of Engineering (India)
Ramya S K, SJC Institute of Technology (India)
K B Raja, UVCE (India)
Venugopal K. R., Univ. Visvesvaraya (India)
L. M. Patnaik, Indian Institute of Science (India)


Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Antanas Verikas; Jianhong Zhou, Editor(s)

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