Abstract. The license plate recognition usually used as part of system such as parking system. License plate detection considered as the most important step in the license plate recognition system. We propose methods that can be used to detect the vehicle plate on mobile phone. In this paper, we used Sliding Window, Histogram of Oriented Gradient (HOG), and Support Vector Machines (SVM) method to license plate detection so it will increase the detection level even though the image is not in a good quality. The image proceed by Sliding Window method in order to find plate position. Feature extraction in every window movement had been done by HOG and SVM method. Good result had shown in this research, which is 96% of accuracy.

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In general, the vehicle number plate detection system in an image should be able to overcome two problems, first how to determine the position of the vehicle number plate or which vehicle number plate is on an image and the second how big is the plate. A number of vehicle license plate detection methods have been proposed over the past two decades, and some have shown success in certain tasks. This study will detect the license plate number of vehicles using the CNN. The initial process is to create a training data license plate numbers using CNN processed on the server. Furthermore, the training data entered on the vehicle license plate detection applications. Vehicle license plate detection results will be displayed in percent accuracy. Based on the testing, the results obtained were very satisfactory with the accuracy of detection of vehicle license numbers as much as 98.19%, the remaining 1.81% of the plates were detected but not the image of the plate that was cropped. It shows that the method has been implemented on CNN that training data and license plate detection is very pretty accurate in detecting vehicle license plate. Implementation of CNN methods on android based mobile devices for data processing training and detection testing of vehicle license plate shows very satisfactory results.