Handwritten Chinese character text image correction method based on block similarity
Yong Yang, Kaiwen Wang, Fuheng Qu, Yuetao Pan, Haoji Shan · 2023
Text image aberration correction, as a pre-processing step in Chinese character image processing techniques, has an important impact on its final results. The existing methods are difficult to obtain satisfactory correction results for text images of handwritten Chinese characters due to the non-uniform types of aberrations. To address this problem, a new correction method is proposed in this paper. The method uses Pearson correlation coefficients to classify text lines based on text line trends and combines document distortion models to unify text lines with different distortion types; meanwhile, a data expansion method based on historical text information is proposed to transform the irregular text line correction problem into a model-based text block optimization problem to deal with the situation where the number of text images is small, resulting in insufficient information for distortion models. situation. The comparison experiments with existing methods on synthetic and real datasets show that the method in this paper has better visual correction effect and higher values of PSNR, SSIM and MS-SSIM evaluation indexes.