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Scene text detection method based on the hierarchical model
As an important step in textâbased information extraction systems, scene text detection has become a popular subject of research in recent years. In this study, the authors present a novel approach to robustly detect texts which are variable in scales, colours, fonts, languages and orientations in scene images. To segment candidate text connected components (CCs) from images, both local contrast and colour consistency are considered in superpixel level. To filter out the nonâtext CCs, a hierarchical model is designed. This hierarchical model groups the CCs into three cascaded stages, and is equipped with a wellâdesigned classifier in each stage. Experimental results on the public ICDAR 2005 dataset and the MSRAâTD500 dataset show that their approach obtains better performance than other stateâofâtheâart methods