An image correction method based on corner point detection
Weiqin Huang, Yikai Gu, Yulong Fu, Yongfu Li, Yue Han · 2022
To better achieve image correction effect, an image correction method based on corner point detection is proposed. In image preprocessing, firstly, image equalization is achieved based on the contrast limited adaptive histgram equalization to avoid the problems caused by illumination and suppress noise while maintaining details, and then adaptive threshold segmentation is performed using the OTSU to obtain the binarized image. In the corner point detection stage, the contours of the binarized image are extracted firstly and the closed contours are filled to avoid the independent contours from affecting the accuracy of region growth, then the center point of the image is used as the seed pixel for region growth, and finally the four corner points are calculated based on the linear contours of the growth region and Hough theory, where the accurate region growth result can avoid the influence of the background on the corner point detection. In the correction stage, the perspective matrix is calculated by the four corner points, and the image is corrected by the perspective transformation. The experiments show that the proposed method can accurately find the corner points of document images and achieve efficient correction.