We are pleased to announce that the following paper has been accepted in the 21st International Conference on Image Processing (ICIP'14). A precise skew estimation algorithm for document images using KNN clustering and Fourier transform Jonathan Fabrizio EPITA Research and Development Laboratory (LRDE) jonathan.fabrizio@lrde.epita.fr In this article, we propose a simple and precise skew estimation algorithm for binarized document images. The estimation is performed in the frequency domain. To get a precise result, the Fourier transform is not applied to the document itself but the document is preprocessed: all regions of the document are clustered using a KNN and contours of grouped regions are smoothed using the convex hull to form more regular shapes, with better orientation. No assumption has been made concerning the nature or the content of the document. This method has been shown to be very accurate and was ranked first at the DISEC’13 contest, during the ICDAR competitions. -- Edwin Carlinet Doctorant à l'Université Paris-Est / EPITA