Identify anomalies in complex places using genetic algorithm optimization

Since surveillance with the human eye may be wrong, so it should be used in the field of intelligent systems to reduce the possibility of error, in addition surveillance costs will also be reduced. Visual surveillance in different algorithms have been proposed, each has their own advantages and disadvantages. The advantages of this algorithm can be used to accurately diagnose abnormalities and disadvantages of requiring expensive hardware can be mentioned. In this paper, improved genetic algorithm to detect anomalies in the image is used and outputs of the proposed algorithm with some of the methods in this field are compared.

Keywords:

surveillance , anomalies , genetic algorithm