Description

Local edge-based descriptors have gained much attention as feature extraction methods for facial expression recognition. We propose a novel edge-based descriptor, named Local Prominent Directional Pattern (LPDP), which considers statistical information of a pixel neighborhood to encode more meaningful and reliable information than the existing descriptors for feature extraction. LPDP examines a local neighborhood of a pixel to retrieve significant edges corresponding to the local shape and thereby ensures encoding edge information in spite of some positional variations and avoiding noisy edges