Document classification for copy-mode decision

We proposed a low-complexity document classification algorithm to select copy mode. The goal is to select a suitable copy mode during copying process. We first analyzed scanned images and classified them into three modes: text, image, mixed modes. To classify images, we used several features, which include pixel density with low brightness, edge length and text line components. Experimental results showed that the proposed algorithm provided about 95% classification accuracy.