Indonesian License Plate Recognition with Improved Horizontal-Vertical Edge Projection

Imam Nududdin, Ida Nurhaida


License Plate Recognition (LPR) is one of the classical problems in the field of object recognition. Its application is very crucial in the automation of transportation system since it helps to recognize a vehicle identity, which information is stored in the license plate. LPR usually consists of three major phases: pre-processing, license plate localization, optical character recognition (OCR). Despite being classical, its implementation faced with much more complex problems in the real scenario, mainly caused by natural lighting, specular reflection in the vehicle body, and object with high saturation intensity. This paper proposed an improved LPR algorithm based on modified Horizontal-Vertical Edge Projection. It is used to detect and localize the region of interest by doing such analysis along the horizontal and vertical projection of the image. Related works proved that the modified Horizontal Vertical Edge Projection is the simplest method to be implemented, yet very effective against Indonesian license plate. However, its performance gets reduced when specular reflection is occurred in the sample image. Therefore, morphological operations are utilized in the pre-processing phase to reduce the effects of specular reflection and high saturation intensity, while preserving the needed information to detect region of interest. Based on the experimental results, our proposed algorithm shows an improvement compared with the previous research and successfully detect 71 license plates in 80 image samples which results in 88.75% accuracy.


license plate recognition; morphology operation; image processing; computer vision

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