Detection and Recognition of Myanmar Characters from the Dissimilar Images
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Abstract
The impartial of this paper is to spread the License Plate Recognition for the traffic light development of Myanmar. In this paper, image processing toolbox, controlling and take boxes were proposed to extract the numbers and characters from the input images. Our method consists of three steps. In the first step, the input license plate image is increased by doing some the action or noise modification. Then the features of the characters are extracted to overcome the sameness problems of the Myanmar characters. Finally, neural network is used for the character recognition. The experiments were carried out on the dissimilar Myanmar vehicle images and results showed the efficiency of 93% which was substantially applied for the license plate detection, letters and numbers extraction.
