The license plate has a serial number of letters and numbers arranged in the vehicle. In Indonesia, personal number plates use black base color with white characters. The license plate has characters that represented data of the vehicle. License plate is become a way to differentiate identity of vehicle. From the character in license plate, we can know the owner of the vehicle.

Ticketing system on the parking area in shopping mall and offices have a way to write the license plate by the manual and automatic. In the manual parking system, the officer records the ticket number according to the license plate of the vehicle. Until now, the available system is taking a plate with the camera image and will be displayed on the ticket of the bar code but not to recognize the contents of the license plate of the vehicle. From these problems, came the idea to detect vehicle license plate and at the entrance of the parking lot automatically. This system will allow parking attendants to match the license plate on the vehicle.

Many methods that can be used to detect the characters of car license plate. The methods that researches be used to detect the characters are active contour and template matching. These segmentation methods will get the character of car license plate. After being segmented, the characters will be compared in 3 conditions that are accuracy, specificity and sensitivity. These conditions will be passed after the segmented images are compared with the character databases. The comparasion got pixels in any condition, namely True Positive, True Negative, False Positive and False Negative. License plate recognition use neural network techniques to enhance its computing capability.

The performance of accuracy, specificity and sensitivity, compared between Active Contour and Template Matching. This research show that active contour play better performance than template matching.