Scene text extraction in natural scene images using hierarchical feature combining and verification
- Authors
- Kim K.C.; Byun H.R.; Song Y.J.; Choi Y.W.; Chi S.Y.; Kim K.K.; Chung Y.K.
- Issue Date
- Sep-2004
- Publisher
- IEEE
- Citation
- Proceedings - International Conference on Pattern Recognition, v.2, pp 679 - 682
- Pages
- 4
- Journal Title
- Proceedings - International Conference on Pattern Recognition
- Volume
- 2
- Start Page
- 679
- End Page
- 682
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/16118
- DOI
- 10.1109/ICPR.2004.1334350
- ISSN
- 1051-4651
- 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.
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