An algorithm for colour-based natural scene text segmentation

Chao Zeng, Wenjing Jia, Xiangjian He

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

6 Citations (Scopus)


Before the step for text recognition, a text image needs to be segmented into foreground containing only the text area and background. In this paper, a method is proposed for segmenting colour natural scene texts which suffer from a wide range of degradations with complex background. A text image is firstly processed by two 3-means clustering operations with different distance measurements. Then, a modified connected component (CC)-based validation method is used to obtain the text area after clustering. Thirdly, a proposed objective segmentation evaluation method is utilised to choose the final segmentation result from the two segmented text images. The proposed method is compared with other existing methods based on the ICDAR2003 public database. Experimental results show the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationCamera-Based Document Analysis and Recognition - 4th International Workshop, CBDAR 2011, Revised Selected Papers
Number of pages11
Publication statusPublished - 2012
Externally publishedYes
Event4th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2011 - Beijing, China
Duration: 22 Sept 201122 Sept 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7139 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2011


  • connected component analysis (CCA)
  • k-means clustering
  • natural scene text segmentation
  • segmentation evaluation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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