5. Conclusion Facial recognition systems can be used in various ways to prevent crimes. One of these ways is using FaceIt. FaceIt is a face recognition system that can search through a crowd for a face and match this face with the mugshot history of this specific person. It is considered to be the most accurate facial recognition software as of today. Other results are: matching faces from live security images, face recognition in photographs and face recognition from sketches. These are all methods in which a face (of e.g. a possible criminal) is compared to a face in respectively live security images, photographs and sketches, to see if there is a match. The facial recognition system is far from perfect. There are still a lot of dangers that need to be considered. Some of the risks that facial recognition brings are: the increasing of crime opportunities, the possibility of falsely accusing innocent people and a loss of privacy. From this paper can be concluded that facial recognition creates a lot of opportunities to help prevent crime. However, there are still a lot of difficulties that can cause problem when these techniques are used in the real world. Further research Further research can be done in different ways. There are still a lot of ethical questions that need to be answered. A trade-off between privacy and the security of facial recognition systems needs to be found. Further research in this ethical field is necessary to understand the impact implementing facial recognition in the prevention of everyday criminality has. To really understand facial recognition, the different methods and algorithms that can be used for facial recognition should be analyzed and compared with each other. This way, it should be easier to get an image of what facial recognition is and in what ways it can help with preventing crime.>