A Scene Text Detector for Text with Arbitrary Shapes

Weijia Wu, Jici Xing, Cheng Yang, Yuxing Wang and Hong Zhou

Mathematical Problems in Engineering, 2020, vol. 2020, 1-11

Abstract:

The performance of text detection is crucial for the subsequent recognition task. Currently, the accuracy of the text detector still needs further improvement, particularly those with irregular shapes in a complex environment. We propose a pixel-wise method based on instance segmentation for scene text detection. Specifically, a text instance is split into five components: a Text Skeleton and four Directional Pixel Regions, then restoring itself based on these elements and receiving supplementary information from other areas when one fails. Besides, a Confidence Scoring Mechanism is designed to filter characters similar to text instances. Experiments on several challenging benchmarks demonstrate that our method achieves state-of-the-art results in scene text detection with an F-measure of 84.6% on Total-Text and 86.3% on CTW1500.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8916028

DOI: 10.1155/2020/8916028

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