i. Which facial recognition technologies exist? A numerous of facial recognition techniques and methods are being used for security and authentication purposes which includes areas in detective agencies and military purposes[25]. This way, the facial recognition techniques can play a role in preventing crime. There are multiple methods considered the two primary tasks of facial recognition, i.e. verification and identification. Verification, also called authentication, is presenting a face image of an unknown individual along with a claim of identity, and then ascertaining whether the individual is who he/she claims to be. Identification, also called recognition, is presenting an image of an unknown individual and determining that person’s identity by comparing that image with a database of images of known individuals[15]. There are even some facial recognition techniques that are able to see emotions. These techniques, as well as verification and identification are of great importance when it comes to finding criminals so crime can be prevented. A few examples of the many methods and algorithm that can be used within the field of facial recognition are: Geometric Feature Based Methods, Template Based Methods, Correlation Based Methods, Matching, Pursuit Based Methods, Singular Value Decomposition Based Methods, The Dynamic Link, Matching Methods, Illumination Invariant Processing Methods, Support Vector Machine Approach, Karhunen- Loeve Expansion Based Methods, Feature Based Methods, Neural Network Based Algorithms and Model Based Methods [25]. Later on, one of the most known methods will be discussed in a detailed way. The facial recognition methods that can be used, all have a different approach. Some are more frequently used for facial recognition algorithms than others. The use of a method also depends on the needed applications. For instance, surveillance applications may best be served by capturing face images by means of a video camera while image database investigations may require static intensity images taken by a standard camera. Some other applications, such as access to top security domains, may even necessitate the forgoing of the nonintrusive quality of face recognition by requiring the user to stand in front of a 3D scanner or an infrared sensor[15]. Consequently, there can be concluded that there can be made a division of three groups of face recognition techniques, depending on the wanted type of data results, i.e. methods that compar>