Local directional double ternary coding pattern for facial expression recognition
Chebah Ouafa, Laskri Mohamed Tayeb · International Journal of Computational Vision and Robotics · 2023
This paper presents a novel texture descriptor, the local directional double ternary coding pattern (LDDTCP) that combines the directional information from LDP and the ternary description from LTP for representing facial expression. The proposed LDDTCP operator encodes the image texture by computing the edge and line responses values using the 8-direction-based Frei-Chen masks. To achieve robustness, the obtained eight Frei-Chen masks are partitioned into two groups according to their directions. After calculating the average of each group, we assign three discrimination levels to each pixel based on the edge responses values in the first group and the line response values in the second group, obtaining LDDTCP-1 and LDDTCP-2 codes, respectively. The last feature descriptor vector LDDTCP is formed by concatenation of both LDDTCP-1 and LDDTCP-2 histograms. Experimental results using the CK and JAFFE database show that the LDDTCP descriptor achieves superior recognition performance compared to some existing local descriptor methods.