Split and Merge: Component Based Segmentation Network for Text Detection

Pan Gao, Qi Wan, Linlin Shen

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a novel component-based detector to locate scene texts with arbitrary orientations, shapes and lengths. Our approach detects text by predicting four components like text region (TR), text skeleton (TS), text sub-region (TSR) and text connector (TC). TR and TS can well separate adjacent text instance. TSR are merged by TC to form a complete text instance. Experimental results show that the proposed approach outperforms state-of-the-art methods on two curved text datasets, i.e. 82.42% and 82.63% F-measures were achieved for the Total-Text and CTW1500, respectively. Our approach also achieves competitive performance on multi-oriented dataset, i.e. 85.86% f-measure for the ICDAR2015 was achieved.

Original languageEnglish
Title of host publicationPattern Recognition and Artificial Intelligence - International Conference, ICPRAI 2020, Proceedings
EditorsYue Lu, Nicole Vincent, Pong Chi Yuen, Wei-Shi Zheng, Farida Cheriet, Ching Y. Suen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages14-27
Number of pages14
ISBN (Print)9783030598297
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event2nd International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2020 - Zhongshan, China
Duration: 19 Oct 202023 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12068 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2020
Country/TerritoryChina
CityZhongshan
Period19/10/2023/10/20

Keywords

  • Arbitrary shape
  • Scene image
  • Text detection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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