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http://dx.doi.org/10.5909/JBE.2020.25.2.275

Proposal for Deep Learning based Character Recognition System by Virtual Data Generation  

Lee, Seungju (Dept. of Media IT Engineering, The Graduate School, Seoul National University of Science and Technology)
Park, Gooman (Dept. of Electronic IT Media Engineering, Seoul National University of Science and Technology)
Publication Information
Journal of Broadcast Engineering / v.25, no.2, 2020 , pp. 275-278 More about this Journal
Abstract
In this paper, we proposed a deep learning based character recognition system through virtual data generation. In order to secure the learning data that takes the largest weight in supervised learning, virtual data was created. Also, after creating virtual data, data generalization was performed to cope with various data by using augmentation parameter. Finally, the learning data composition generated data by assigning various values to augmentation parameter and font parameter. Test data for measuring the character recognition performance was constructed by cropping the text area from the actual image data. The test data was augmented considering the image distortion that may occur in real environment. Deep learning algorithm uses YOLO v3 which performs detection in real time. Inference result outputs the final detection result through post-processing.
Keywords
YOLO; Virtual Data Generation; Object Detection; Text Recognition;
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