Robust Facial Marks Detection Method Using AAM And SURF

In face recognition technology, facial marks identification method is one of the unique facial identification tasks using soft biometrics. Also facial marks information can enhance the face matching score to improve the face recognition performance. As numbers of folk apply their face with cosmetic items, some of the facial marks are invisible or hidden from their faces. In the literature, they used AAM (Active Appearance Model) and LoG (Laplacian of Gaussian) method to detect the facial marks. However, to the best of our knowledge, the methods related to the detection of facial marks are poor in performance in cosmetic applied faces. In this paper, we propose robust method to detect the facial marks such as tattoos, scars, freckles and moles etc. Initially we apply active appearance model (AAM) for facial feature detection purpose. In addition to this prior model we apply Canny edge detector method to detect the facial mark edges. Finally SURF is used to detect the hidden facial marks which are covered by cosmetic items. Hence we argue that the choice of this method gives high accuracy in facial marks detection of the cosmetic applied faces. In fact the use of robust marks detection method with soft biometrics traits performed the best facial recognition technology.