Scene Text Extraction in Natural Scene Images using Hierarchical Feature Combining and Verification

Authors:
K. C. Kim;H. R. Byun;Y. J. Song;Y. W. Choi;S. Y. Chi;K. K. Kim;Y. K. Chung
Affiliations:
Yonsei University, Korea;Yonsei University, Korea;Sookmyung Women's University, Korea;Sookmyung Women's University, Korea;Electronics and Telecommunications Research Institute, Korea;Electronics and Telecommunications Research Institute, Korea;Electronics and Telecommunications Research Institute, Korea
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Year:
2004

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Abstract

We propose a method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature. Then the two level features are combined hierarchically. The low-level features are color continuity, gray-level variation and color variance. The color continuity is used since most of the characters in a text region have the same color, and the gray-level variation is used since the text strokes are distinctive to the background in their gray-level values. Also, the color variance is used since the text strokes are distinctive in their colors to the background, and this value is more sensitive than the gray-level variations. As a high level feature, text stroke is examined using multi-resolution wavelet transforms on local image areas and the feature vector is input to a SVM(Support Vector Machine) for verification. We tested the proposed method with various kinds of the natural scene images and confirmed that extraction rates are high even in complex images.