Nakisa Abounasr - Department of Electrical Engineering Najafabad Branch, Islamic Azad University
Hossein Pourghassem - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University,

This paper presents two new approaches for facialexpression recognition based on digital curvelet transform andlocal binary patterns from three orthogonal planes (LBP-TOP)for both still image and image sequences. The features areextracted by using the digital curvelet transform on facial regionsin still image. In this approach, some sub-bands correspond toangle of facial region is used. These sub-bands consist of morefrequency information. The digital curvelet coefficients and LBPTOPare represented to combine spatio-temporal and spectralfeatures for image sequences. The obtained results by ourproposed approaches on the Cohn-Kanade facial expressiondatabase have acceptable recognition rates of 91.90% and88.38% for still image and image sequences, respectively.

facial expression recognition; digital curvelet transform (DCUT); local binary patterns from three orthogonal planes (LBP_TOP)