Abstract
Scene text in the wild is commonly presented with
high variant characteristics. Using quadrilateral
bounding box to localize the text instance is nearly indispensable for detection methods. However, recent researches reveal that introducing quadrilateral bounding box for scene text detection will
bring a label confusion issue which is easily overlooked, and this issue may significantly undermine
the detection performance. To address this issue,
in this paper, we propose a novel method called
Sequential-free Box Discretization (SBD) by discretizing the bounding box into key edges (KE)
which can further derive more effective methods to improve detection performance. Experiments
showed that the proposed method can outperform state-of-the-art methods in many popular scene
text benchmarks, including ICDAR 2015, MLT,
and MSRA-TD500. Ablation study also showed
that simply integrating the SBD into Mask R-CNN
framework, the detection performance can be substantially improved. Furthermore, an experiment on the general object dataset HRSC2016 (multioriented ships) showed that our method can outperform recent state-of-the-art methods by a large
margin, demonstrating its powerful generalization
ability