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http://dx.doi.org/10.3745/KIPSTB.2004.11B.6.667

Text Region Verification in Natural Scene Images using Multi-resolution Wavelet Transform and Support Vector Machine  

Bae Kyungsook (한국전자통신연구원 지능형로봇연구단)
Choi Youngwoo (숙명여자대학교 정보과학부)
Publication Information
The KIPS Transactions:PartB / v.11B, no.6, 2004 , pp. 667-674 More about this Journal
Abstract
Extraction of texts from images is a fundamental and important problem to understand the images. This paper suggests a text region verification method by statistical means of stroke features of the characters. The method extracts 36 dimensional features from $16\times16$sized text and non-text images using wavelet transform - these 36 dimensional features express stroke and direction of characters - and select 12 sub-features out of 36 dimensional features which yield adequate separation between classes. After selecting the features, SVM trains the selected features. For the verification of the text region, each $16\times16$image block is scanned and classified as text or non-text. Then, the text region is finally decided as text region or non-text region. The proposed method is able to verify text regions which can hardly be distin guished.
Keywords
Wavelet Transform; SVM; Bayesian Error Rate; Verification;
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