Scene text detection based on component-level fusion and region-level verification

In this paper, we present a novel scene text detection method that combines the advantages of component-based methods and region-based methods, while overcoming their inherent limitations. We first extract text regions as candidates, and then aggregate these text components in these regions into words and text lines. To separate non-text components in the background from text components, we perform both character-level filtering and word-level classification with a trained linear SVM (support vector machine) classifier. Our extensive experiments on ICDAR2003 and ICDAR2011 datasets have shown that our method outperforms the state-of-the-art methods in text detection.