PENERAPAN HOUGH TRANSFORM, CONNECTED COMPONENT LABELING DAN TEMPLATE MATCHING UNTUK PENGENALAN KARAKTER PLAT KENDARAAN
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Abstract
Vehicle license plates are the identities of motor vehicles that are often used for record-keeping when using paid parking lots. Recording vehicle license plates requires the application of information technology so that parking service administration is more efficient and free from recording errors. Information technology offers the application of OCR (Optical Character Recognition) methods to help the process of recording characters found on vehicle license plates. OCR has many techniques that can help the character recognition process, starting from the initial image capture process to the recognition stage. The initial image stage after being captured is to perform the initial image processing process by converting the image, determining the vehicle license plate area in the vehicle image, performing character labeling and segmentation on the plate image, and performing character recognition. The approach to character recognition on vehicle license plates that will be used is Hough Transform for determining the vehicle license plate area, character labeling and segmentation with Connected Component Labeling, and Template Matching as a character recognition method. The vehicle license plate character recognition model was tested with a scenario of 25 images captured directly from the parking lot. The test results produced Hough Transform and Connected Component Labeling could determine the vehicle license plate area and perform character labeling and segmentation on the vehicle license plate. Whereas in the template matching stage, the character recognition accuracy on 25 vehicle license plates was 94%. Other findings in this study are that the lighting conditions of the image environment, the number of images that become the database, and the condition of the paint of motor vehicle license plates can improve accuracy.
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