Facial expression recognition using weber discrete wavelet transform

Article type: Research Article

Authors: Nazir, Muhammad^{a; b; *} | Jan, Zahoor^a | Sajjad, Muhammad^a

Affiliations: [a] Digital Image Processing Laboratory, Department of Computer Science, Islamia College Peshawar, Pakistan | [b] Department of Computer Science and Engineering, HITEC University Taxila, Pakistan

Correspondence: [*] Corresponding author. Muhammad Nazir, Department of Computer Science and Engineering, HITEC University Taxila, Pakistan. Tel.: +92 3335263675; E-mail: muhammad.nazir@hitecuni.edu.pk.

Abstract: In this paper, a novel descriptor called Weber Discrete Wavelet Transform (WDWT) is proposed. It effectively recognizes facial expressions. WDWT uses unique combination of Weber Local Descriptor (WLD) and Discrete Wavelet Transform (DWT) for efficient extraction of illumination invariant features from multi scale images. The proposed descriptor’s effectiveness is evaluated under different challenges on facial expression recognition problem. Experiments are performed on the standard face databases and results show that the proposed technique performs better than traditional LBP and WLD over a range of low resolution images. A significant decrease in the feature dimensions and substantial increase in recognition accuracy rate has been observed.

Keywords: Facial expression recognition, weber local descriptor, discrete wavelet transform, multi scale images, dimension reduction

DOI: 10.3233/JIFS-161787

Journal: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 1, pp. 479-489, 2017