Face detection: Comparing Haar-like combined with cascade classifiers and Edge Orientation Matching

One of the major research areas attracting much interest is face recognition. This is due to the growing need of detection and recognition in the modern days' industrial applications. However, this need is conditioned with the high performance standards that these applications require in terms of speed and accuracy. In this work we present a comparison between two main techniques of face recognition in unconstraint scenes. The first one is Edge-Orientation Matching and the second technique is Haar-like feature selection combined cascade classifiers.