Hidayati, Shintami C.Shintami C.HidayatiHsu, Che HaoChe HaoHsuSun, Shih WeiShih WeiSunWEN-HUANG CHENGHua, Kai LungKai LungHua2023-03-092023-03-092015-07-289781479970797https://scholars.lib.ntu.edu.tw/handle/123456789/629112When periodic halftoned documents (e.g., books, newspapers, and magazines) are scanned for image reproduction, moiré patterns occur. In order to avoid these moiré artifacts, it is necessary to detect the periodic halftone. This paper provides a fast Fourier transform based method to classify periodic halftoned documents. Experimental results show that the overall accuracy of this method is 97% on a large data set which contains many difficult-to-classify images. Misclassified documents tend to be extremely difficult to classify, in that they contain very small periodic halftone regions. An existing method, by comparison, has accuracy of only 70%.fast Fourier transform | moiré patterns | Periodic halftone noiseconference paper10.1109/ICMEW.2015.71698432-s2.0-84945561218https://api.elsevier.com/content/abstract/scopus_id/84945561218