%0 Journal Article
	%A N. Chaitawittanun and  M. Munlin
	%D 2014
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 86, 2014
	%T An Efficient Clustering Technique for Copy-Paste Attack Detection
	%U https://publications.waset.org/pdf/10001670
	%V 86
	%X Due to rapid advancement of powerful image
processing software, digital images are easy to manipulate and
modify by ordinary people. Lots of digital images are edited for a
specific purpose and more difficult to distinguish form their original
ones. We propose a clustering method to detect a copy-move image
forgery of JPEG, BMP, TIFF, and PNG. The process starts with
reducing the color of the photos. Then, we use the clustering
technique to divide information of measuring data by Hausdorff
Distance. The result shows that the purposed methods is capable of
inspecting the image file and correctly identify the forgery.

	%P 394 - 402