Document segmentation using texture variance and low resolution images

Abstract

This paper describes a document segmentation method based on segmentation by texture using low resolution gray level images. The method is derived from the human vision perception theory. The concepts used from this theory are, global to local processing and low resolution information. If a document is viewed at a certain distance far from a person, the person sees a blurred image of the document, but is still able to detect the different blocks of the document. Detection is possible since each block has a specific texture pattern. These patterns correspond to regions of text, regions of graphics and regions of pictures. Thus the theory to prove is that a document image can be segmented into regions of text, and regions of graphics and/or pictures using the texture of low resolution images. The method presented in this paper, despite its simplicity, has shown to be effective and robust. It was designed to work with free format documents, text in background other than white, skew greater than 10 degrees. It requires less computation than the segmentation methods using texture described in other papers.