Extracting halftones from printed documents using texture analysis

Separating halftones from text is an important step in document analysis. We present an algorithm that accurately extracts halftones from other information in printed documents. We treat halftone extraction as a texture-segmentation problem. We show that commonly used halftones, consisting of a pattern of dots, can be viewed as a texture. This texture exhibits a distinct spectral component that can be detected using a properly tuned Gabor filter. The Gabor filter essentially transforms halftones into high-contrast regions that can be easily segmented by thresholding. We propose a filter design procedure and provide experimental results. (C) 1997 Society of Photo-Optical Instrumentation Engineers.