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mentioned earlier, there is a long list of methods that can be used for facial recognition. Four of them, i.e Eigenface Method, Correlation Method, Fisherface Method and the Linear Subspaces Method, are the most favorite. Below here, you can find the error rates of those four methods, considered pictures with close crop or the whole face. Figure 3: Graph and table of the result of an experiment with the four most used facial recognition techniques [1] As you can see, the Eigenface Method has the most errors, and the Fisherface Method the least. You can also see that the error rate is higher with images of close crops faces, compared to a full face image. This shows that it is harder for a facial recognition algorithm to recognize someone if their face is not fully shown in the picture and the features are thus not recognized. It also reminds us of the fact that facial recognition techniques are not completely accurate. Hopefully they will become more accurate in the future, so e.g crime can be prevented faster and better. 3. Results of face recognition technologies in crime prevention There are many ways for law enforcement to help them with decreasing the amount of crime. Face recognition has a big role in human life. Witnesses can describe a person’s face. Also, the citizenry can help by sending in photos. But an Artificial Intelligence can also do face recognition. It can search through a database full of mug shots to find a match with the face from an image or sketch. The Artificial Intelligence will take much shorter time to find a match than a group of officers or even specialists. In the following part, there will be discussed how four different approaches are all playing a role in crime prevention. i. FaceIt In the department of law enforcement, there is FaceIt, a face recognition system that can search through a whole crowd for a face and match this face with the mugshot history of this specific person. FaceIt is considered to be the most accurate facial recognition software as of today [11]. This face recognition system is mostly used by law enforcement agencies. Next to being used for law enforcement and security surveillance, which is the primary use of it, the system can also be used for computer security and eliminating fraud. Eliminating fraud is very useful in a situation as voting in a presidential election. By using this technology, voting multiple times can be evaded and people can’t get away with it anymore. People’s faces will be stored in a database and if a face ap
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