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To identify a vehicle, License Plate identification technology is the key technology of intelligent transport system, finding a stolen vehicle, monitoring traffic flow, in town management, highway tolls etc. The major issue in such applications is to detect the exact location of plate, because finding the location of number plate could vary and as well as its size and color; many of the vehicles have an uncertain difference in License plate position, location and unclean License Plate. In this paper we have conducted a very fresh survey of most authentic techniques of license plate detection from a car, we studied different techniques and compared them; we figured out every technique has its own limitations, every method gives best results under some certain conditions so do bad results, we figured out all we need to do is to have locus of control, we shall control theenvironment we are working in, some techniques works good in dark light, some for bright light etc; every technique has its own parameters to identify license plate; this paper will lead you to choose the best technique for detection just according to your circumstance.

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Abstract-Due to popularity of the World Wide Web and ecommerce, electronic communications between people and different organizations through virtual world of the Internet have provided a good basis for commercial and economic relations. These developments, although occurring for less than a century, electronic communications have always been subject to interference, cheating, fraud, and other acts of sabotage. Along with this increase in trading volume, there is a huge increase in the number of online fraud which results in billions of dollars of losses annually worldwide; this has a direct effect on customer service of banking systems, particularly electronic banking systems, and survival as a reliable financial service provider. Therefore, attention to fraud detection techniques is essential to prevent fraudulent acts and is the motive for many scientific researches. For this reason, business intelligence is used to identify financial violations in various economic, banking and other fields. Here, the focus is on algorithms and methods presented in data mining to deal with fraud by using neural networks. The main objective is to improve these methods or present new algorithms by studying the behavioral patterns of customers and the combined use of genetic algorithm to improve the performance of neural network and find the appropriate models for better decision making by implementing and testing the performance of the suggested algorithms. The results show that more strength was given to neural network by using genetic algorithm. In fact, genetic algorithm can raise our ability to control the training process. Moreover, it was concluded that criteria such as age, gender, marital status were not effective on detection; in fact, the most important effective criteria are information related to transaction.

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