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.