Text detection in images based on color texture features

Authors:
Chunmei Liu;Chunheng Wang;Ruwei Dai
Affiliations:
Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Year:
2005

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Abstract

In this paper, an algorithm is proposed for detecting texts in images and video frames. Firstly, it uses the variances and covariancs on the wavelet coefficients of different color channels as color textural features to characterize text and non-text areas. Secondly, the k-means algorithm is chosen to classify the image into text candidates and background. Finally, the detected text candidates undergo the empirical rules analysis to identify text areas and project profile analysis to refine their localization. Experimental results demonstrate that the proposed approach could efficiently be used as an automatic text detection system, which is robust for font-size, font-color, background complexity and language.