Text region extraction and text segmentation on camera-captured document style images

Y. J. Song, K. C. Kim, Y. W. Choi, H. R. Byun, S. H. Kim, S. Y. Chi, D. K. Jang, Y. K. Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

In this paper, we propose a text extraction method from camera-captured document style images and propose a text segmentation method based on a color clustering method. The proposed extraction method detects text regions from the images using two low-level image features and verifies the regions through a high-level text stroke feature. The two level features are combined hierarchically, The low-level features are intensity variation and color variance. And, we use text strokes as a high-level feature using multi-resolution wavelet transforms on local image areas. The stroke feature vector is an input to a SVM (Support Vector Machine) for verification, when needed. The proposed text segmentation method uses color clustering to the extracted text regions. We improved K-means clustering method and it selects K and initial seed values automatically. We tested the proposed methods with various document style images captured by three different cameras. We confirmed that the extraction rates are good enough to be used in real-life applications.

Original languageEnglish
Title of host publicationProceedings of the Eighth International Conference on Document Analysis and Recognition
Pages172-176
Number of pages5
DOIs
Publication statusPublished - 2005
Event8th International Conference on Document Analysis and Recognition - Seoul, Korea, Republic of
Duration: 2005 Aug 312005 Sept 1

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2005
ISSN (Print)1520-5363

Other

Other8th International Conference on Document Analysis and Recognition
Country/TerritoryKorea, Republic of
CitySeoul
Period05/8/3105/9/1

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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