Automatic Detection and Recognition of Car Plates Based on Cascade Classifier

Noor M.  Hashem; Heba Kh.  Abbas

doi:10.30526/36.1.2895

Authors

Noor M. Hashem university of Baghdad /college of science woman
Heba Kh. Abbas

DOI:

https://doi.org/10.30526/36.1.2895

Keywords:

cascade classifier, Viola-Jones, training file, positive file and car plate detection.

Abstract

The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the accuracy was 99.8%.

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