Automatic Detection of Facial Midline And Its Contributions To Facial Feature Extraction

Abstract

We propose a novel approach for detection of the facial midline from a frontal face image. Using midline as a guide reduces computational cost required for facial feature extraction (FFE) because the midline is capable of restricting multi-dimensional searching process into one-dimensional search. The proposed method detects the facial midline from an edge image as the symmetry axis using the generalized Hough transformation. Experimental results on the FERET database indicate that the proposed algorithm can accurately detect facial midlines over many different scales and rotation. The total computational time for facial feature extraction has been reduced by a factor of 280 using the midline detected by this method.