关键词: 变形文档图像, 文本域轮廓检测, PCA, 最小化重投影, 文档图像校正

Abstract: Distorted document images usually appear in smartphone images, which causes a lot of inconvenience for users. These images affect text recognition, post-processing, etc. Existing distorted document image correction methods have some limitations such as single correction type and unsatisfactory correction effect. To solve the above problems, an distorted document image correction method based on minimizing re-projection is proposed. Firstly, the connected domain of text lines is obtained by detecting text field contour and merging text field contour. Secondly, PCA (Principal Component 
Ana- lysis) is adopted to generate key points of text in the connected domain of the row. Finally, resampled parameters are obtained by minimizing the distance between the key points and their projection points. The distorted pages are re-projected to minimize the document image correction. After correction, the recognition rate is effectively improved. Compared with the existing methods, a better recognition effect is achieved. Moreover, ablation experiments are used to verify the improvement effect of text field merging and minimization re-projection on the recognition performance respectively.

Key words: distorted document image, text field contour detection, PCA, minimizes re-projection, document image correction