A new textual/non-textual classifier for document skew correction
Xiaoyan Zhu, Xiaoxin Yin · 2003
A robust approach is proposed for document skew detection. We use Fourier analysis and SVM to classify textual areas from non-textual areas of documents. We also propose a robust method to determine the skew angle from textual areas. Our approach achieves good performance on documents with large area of non-textual contents.