VIETNAMESE SCENE TEXT DETECTION METHOD BASED ON DEEP LEARNING

VIETNAMESE SCENE TEXT DETECTION METHOD BASED ON DEEP LEARNING

  • Nguyen Thi Thanh Tan EPU
Keywords: Scene text, scene images, text regions, segmentation, detection, features, mapping, accuracy, recall, harmonic mean, convolution, scale, batch, batch normalization

Abstract

This paper proposes an efficient method for detecting Vietnamese text in outdoor scene images. Essentially, the text detection method presented here is based on the idea of utilizing deep learning network architectures to learn various geometric properties to reconstruct polygonal representations of text regions. The effectiveness of the method has been evaluated on four real-world outdoor scene image datasets, including the ICDAR 2015, Total-Text, VinText, and VnSceneText datasets. Experimental results show that the proposed method is capable of detecting text of various shapes and sizes with high and consistent accuracy. Specifically, the method achieved Precision, Recall, and Hmean scores of 87.53%, 86.94%, and 87.23%, respectively, on the test datasets, 84.32%, 88.17%, and 86.20% on a different dataset, 85.63%, 87.94%, and 86.77% on yet another dataset, and 85.14%, 87.23%, and 86.17% on the last dataset. The experimental results indicate that this is a feasible approach for detecting Vietnamese text in outdoor scene images.

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Published
2023-11-26