Parking entrance control using license plate detection and recognition

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Abstract

There is no doubt that car parking is a very challenging and interesting topic of surveillance. In the recent years, a lot of smart systems for parking lot access control were developed to control and register the car data. The aim of this paper is to use image processing methods to control the entrance of a smart parking. The steps of car plate recognition are: preprocessing, License plate detection, character extraction and recognition. In the step of preprocessing, image was enhanced and noise was reduced. After preprocessing stage, color filter was used to detect the plate region. In case of large image size DWT was used for feature extraction and decreased the time of the detection stage. In the stage of character segmentation, the image is converted from grayscale to binary according to a given threshold. Filtering the binary image after using the morphological operation method, the largest objects are determined as the segmented plate characters. Finally, the correlation method was used to recognize the segmented characters. In case of similarity, SVM was used as a good classifier. Experimental results using matlab software, view that the proposed method increase the plate detection and recognition rates. It achieved average 97.8% detection rate, 98% segmentation rate and 97% recognition rate, so it will be a good method for smart parking entrance control.

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APA

Farag, M. S., Mohie El Din, M. M., & El Shenbary, H. A. (2019). Parking entrance control using license plate detection and recognition. Indonesian Journal of Electrical Engineering and Computer Science, 15(1), 476–483. https://doi.org/10.11591/ijeecs.v15.i1.pp476-483

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