Under Fog Weather Vehicle License Processing And Generalized Correlation Detector Enhancement

This paper mainly studies the license plate recognition in fogs as well as the noise-enhanced detection condition for a generalized correlation detector. With the development of industry, the popularity of modern transportation and the gradual deterioration of natural environment, especially the growing appearance of mist, the traffic control has been affected by severely.Firstly, we use the dark channel image dehazing algorithms to make the license plates in fogs clear in this paper. The scale and threshold of log operator is discussed in detail. Detect the processed license plates’ edge with the help of edge detectors. Afterwards, the way of statistical pixels is applied in order to locate the license plates. At last, recognize the characters with the way of template match,In addition, this paper also studies the necessary noise-enhanced weak signal detection condition for a generalized correlation detector. As for the weak signal detection, if the false alarm probability is given, and the observation data is large enough, the detection probability of a generalized correlation detector is a monotonically function of the detector performance enhancement. So, the positive derivative of the efficacy with respect to the noise level is the necessary condition of stochastic resonance. On the basis of this condition, as for the signal detection of scaled-noise, analyze the detector considering in this paper whether there is noise enhancement phenomenon in detail, and shows how to get the corresponding optimal detection performance of noise level equation. The result is of great significance for the development of nonlinear signals processing. In the end, this paper discusses the possibility of noise enhancing the nonlinear detection operators’ edge performance and the preliminary discussion of the edge nonlinear detection operator to deal with the license plates is carried on.