A Novel Unsharp Mask Sharpening Method in Preprocessing for Face Recognition
Lanchi Xie, Jingjing Guo, Zhihui Li · 2015
Face recognition is widely used in public security field. Surveillance video is a major source of probe faces for suspects search. For economic reasons, most social monitors are equipped with analog cameras. When Signals are displayed on PC, interlaced effect will appear. However, after the application of existing methods of de-interlacing, images would lose definition and identification rate would reduce. We proposed a novel sharpening method based on unsharp mask for preprocessing in face recognition. In this paper, we compared different methods of image sharpening. Then we showed the algorithm implementation under the framework of DirectShow. Proposed method makes significant improvement in image clarity and algorithm complexity.