Designing License Plate Identification through Digital Images with OpenCV


Journal Article


The aim of this research is to design and analyze the License Plate Identification program mediated through Digital Images or Automatic Number Plate Recognition (ANPR), especially by using desktop peripheral. In doing so, license plates attached, especially, on cars will be the test subject of this research. The ANPR is already implemented within the barrier gate parking system. It is able to record the data of the vehicles that come in yet it doesnt necessarily recognize or identify the license plates installed on the vehicles. The fundamental goal of the ANPR program itself is actually to utilize digital image identification system in order to identify every single vehicle that goes in and out through the barrier gate parking system. From the result of the experimentation, the ANPR is able to detect and translate the license plates into a form of text in less than one second with 100% accuracy for high quality image, 82.6% for medium quality and 44.5% for low quality image. Series of analysis that the ANPR program situates involves; analysis on the ratio of the license plate, experimentation on the distance of license plate detection process, comparison between binary calculation methods using Adaptive Threshold and Global Threshold, and overall system examination. The result retrieved from the conducted analysis can be considered as a part of the ANPR system


Komarudin A, Satria A. T and Wiedjaja. (2015). Designing License Plate Identification through Digital Images with OpenCV. Procedia Computer Science, 59 (1), 468-472.


Digital images; ANPR; Adaptive Threshold; Global Threshold

Published On

Procedia Computer Science


Abdillah Komarudin

  • Ahmad Teguh Satria
  • Wiedjaja

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