Skew detection of document images by focused nearest-neighbor clustering

Describes an algorithm to estimate the skew angle of document images. It utilizes the nearest-neighbor clustering paradigm. In contrast to earlier approaches, the local clustering process is focused on a subset of plausible neighbors. The proposed skew detection algorithm is potentially usable for any feature points that reveal the dominant orientation of document images in their entirety. Experimental results using connected components and pass codes as features are presented to show the general usefulness of the proposed algorithm