In this paper, we present a document block classification algorithm to automatically classify different types of blocks embedded in a document image. Two kinds of features, density feature and connectivity histogram, are devised to achieve the classification goal. In our approach, segmented document blocks are first classified into text and non-text blocks via the density feature. Then, the connectivity histogram is utilized to further classify non-text blocks into image and graphics blocks. Experimental results reveal the feasibility of the new technique in classifying document blocks.
