A robust algorithm for text detection in color images

Yangxing Liu, Satoshi Goto, Takeshi Ikenaga

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

28 Citations (Scopus)

Abstract

Text detection in color images has become an active research area since recent decades. In this paper, we present a novel approach to accurately detect text in color images possibly with a complex background. First, we use an elaborate edge detection algorithm to extract all possible text edge pixels. Second connected component analysis is employed to construct text candidate region and classify part non-text regions. Third each text candidate region is verified with texture features derived from wavelet domain. Finally, the Expectation maximization algorithm is introduced to binarize text regions to prepare data for recognition. In contrast to previous approach, our algorithm combines both the efficiency of connected component based method and robustness of texture based analysis. Experimental results show that our algorithm is robust in text detection with respect to different character size, orientation, color and language and can provide reliable text binarization result.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Pages399-403
Number of pages5
Volume2005
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event8th International Conference on Document Analysis and Recognition - Seoul
Duration: 2005 Aug 312005 Sep 1

Other

Other8th International Conference on Document Analysis and Recognition
CitySeoul
Period05/8/3105/9/1

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Liu, Y., Goto, S., & Ikenaga, T. (2005). A robust algorithm for text detection in color images. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR (Vol. 2005, pp. 399-403). [1575577] https://doi.org/10.1109/ICDAR.2005.29