Block segmentation and text extraction in mixed text/image documents

Abstract

The segmentation and classification of digitized printed documents into regions of text and images is a necessary first processing step in document analysis systems. It is shown that a constrained run length algorithm is well suited to partition most documents into areas of text lines, solid black lines, and rectangular ☐es enclosing graphics and halftone images. During the processing these areas are labeled and meaningful features are calculated. By making use of the regular appearance of text lines as textured stripes, a linear adaptive classification scheme is constructed to discriminate text regions from others.