Zone classification using texture features

We consider the problem of zone classification in document image processing. Document blocks are labelled as text or nontext using texture features derived from a feature based interaction map (FBIM), a recently introduced general tool for texture analysis. The zone classification procedure proposed is tested on the comprehensive document image database UW-I created at the University of Washington in Seattle. Different classification procedures are considered. The performance ranges from 96% to 98% using 6 FBIM texture features only.