Home > Papers

 
 
WSN: Weighted Segmentation Network for Scene Text Detection
Wei Wenhu,Wang Yulong *
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876;State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876
*Correspondence author
#Submitted by
Subject:
Funding: none
Opened online:17 November 2022
Accepted by: none
Citation: Wei Wenhu,Wang Yulong.WSN: Weighted Segmentation Network for Scene Text Detection[OL]. [17 November 2022] http://en.paper.edu.cn/en_releasepaper/content/4758375
 
 
The detection of arbitrarily shaped scene text is an extremely challenging task. The existing segmentation-based methods have difficulty in distinguishing adjacent text instances and achieve unsatisfactory results. To solve this problem, a novel weighted segmentation network (WSN) that accurately detects text centers and distinguishes adjacent text instances is proposed in this study. In the WSN, a weighted segmentation map is generated by assigning different weights to each pixel in the text area. Then, we extract features from the weighted segmentation map and detect text centers accurately to distinguish adjacent text instances. To train the detector on the weighted segmentation map, we designed a method for annotation generation based on polygon scaling. Extensive experiments on two benchmark datasets, namely Total-Text and CTW-1500, which comprise highly curved texts in natural scene images demonstrated that our WSN can achieve great performance during segmentation-based methods.
Keywords:Scene text detection; Weighted segmentation; Text centers; Polygon scaling
 
 
 

For this paper

  • PDF (0B)
  • ● Revision 0   
  • ● Print this paper
  • ● Recommend this paper to a friend
  • ● Add to my favorite list

    Saved Papers

    Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags

Add yours

Related Papers

Statistics

PDF Downloaded 9
Bookmarked 0
Recommend 0
Comments Array
Submit your papers