Localization of car license plate using adaptive Euler-template matching method

License plate (LP) detection plays an important role in intelligent transportation systems smart traffic control systems of today. Although it is simple and easy to implement for LP detection, traditional template matching method is less favorable compared to state-of-the-art methods due to its processing cost. Thus, this study proposes an innovative template matching method called “adaptive Euler-template matching method” for detection of LP. Two different models of Euler-template and a new matching concept are proposed. The proposed method is evaluated by detecting LP in a total of 150 test images. Then, the performance of proposed method is compared with the performances of some exiting methods. The proposed method gives accuracies of 96% using Euler-template(model-A) and 96.7% using Euler-template(model-B). The average processing time of proposed method is 0.303 s. The results show that Euler-template(model-B) is more effective for LP detection. More distinct observations are presented and finally recommendations for further works are given in this study.