English

TextCohesion: Detecting Text for Arbitrary Shapes

Computer Vision and Pattern Recognition 2019-05-01 v2

Abstract

In this paper, we propose a pixel-wise method named TextCohesion for scene text detection, which splits a text instance into five key components: a Text Skeleton and four Directional Pixel Regions. These components are easier to handle than the entire text instance. A confidence scoring mechanism is designed to filter characters that are similar to text. Our method can integrate text contexts intensively when backgrounds are complex. Experiments on two curved challenging benchmarks demonstrate that TextCohesion outperforms state-of-the-art methods, achieving the F-measure of 84.6% on Total-Text and bfseries86.3% on SCUT-CTW1500.

Keywords

Cite

@article{arxiv.1904.12640,
  title  = {TextCohesion: Detecting Text for Arbitrary Shapes},
  author = {Weijia Wu and Jici Xing and Hong Zhou},
  journal= {arXiv preprint arXiv:1904.12640},
  year   = {2019}
}

Comments

Scene Text Detection Instance Segmentation

R2 v1 2026-06-23T08:52:12.158Z