Extracting Text in Scene Images by Character Region Verification

This paper proposes a method of identifying character-like regions in order to extract and recognize characters in natural color scene images automatically. After connected component extraction based on multi-group decomposition scheme, alignment analysis is used to check the block candidates, namely, the character-like regions in each binary image layer and the final composed image. Priority adaptive segmentation (PAS) is implemented to obtain accurate foreground pixels of the character in each block. Then some heuristic meanings such as statistical features, recognition confidence, and alignment properties, are employed to justify the segmented characters. The algorithms are robust for a wide range of character fonts, shooting conditions, and color backgrounds. Results of our experiments are promising for real applications.