Automatic cropping of images under projective transformation
Julia Shemiakina, Alexander E. Zhukovsky, Ivan A. Konovalenko, Dmitry Nikolaev · 2019
The paper considers the problem of images cropping obtained by projective transformation of source images. The problem is highly relevant to analysis of projective distorted images. We propose two cropping algorithms based on estimation of pixel stretching under the transformation. The algorithms use the ratio of pixel neighborhood areas and the ratio of their chord lengths. The methods comparison is conducted by estimation of cropped background relative areas. The experiment uses real dataset containing projective distorted images of the pages of Russian civil passports. The method based on chord lengths ratio shows better results on highly distorted images.