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 (1946) filter essentially transforms halftones into high-contrast regions that can be isolated by thresholding. We propose a filter-design procedure and provide experimental results.