Character Energy and Link Energy-Based Text Extraction in Scene Images

Extracting text objects from scene images is a challenging problem. In this paper, by investigating the properties of single characters and text objects, we propose a new text extraction approach for scene images. First, character energy is computed based on the similarity of stroke edges to detect candidate character regions, then link energy is calculated based on the spatial relationship and similarity between neighboring candidate character regions to group characters and eliminate false positives. We applied the approach on ICDAR dataset 2003. The experimental results demonstrate the validity of our method.