Rule-based perspective rectification for Chinese text in natural scene images

Recognizing text with large perspective deformation is challenging, especially when the orientation of the text is arbitrary. A rule-based method is proposed in this paper to recover the fronto-parallel image for Chinese text in natural scenes. It relies on the fact that there are many horizontal and vertical strokes in Chinese text and they are accurately or approximately perpendicular to each other in non-italic type. A homography is utilized to describe the relationship between the scene text and its image. Horizontal and vertical strokes are extracted and selected to construct perspective quadrilaterals and the expected rectangles for calculating the homography. Experiments show that the proposed method could rectify the perspective deformation of Chinese text in any orientation effectively and it outperforms the state-of-the-art perspective rectification method based on vanishing point detection.