License plate location is the key technology of license plate recognition. At present license plate color and texture feature were considered in the most license plate location methods

however

these methods had weak adaptability in different environment. In order to solve the problem

firstly

since the fixed color matches of the vehicle license plate

a color matched template matrix was constructed

which was used to restrict the initial edge detected image

so a restricted binary edge image could be obtained. Then

some morphologic operators which have the ability of eliminating noise were applied to form initial localization candidate regions. Finally

according to the texture feature of the license plate

the real license plate area was chosen from candidate regions. BP neural network was adopted to attain the strongly adaptive method which was used to recognize different colors in HSI space. And for shortening the period of location

only the color space in the neighborhood of edge pixels were conversed. The experiment showed that the accurate location of the license plate could be achieved in the complicated environment and different illumination

making use of this method.