A multichannel filtering-based texture segmentation method is applied to a variety of document image processing problems: text-graphics separation, address-block location, and bar code localization. In each of these segmentation problems, the text context or bar code in the image is considered to define a unique texture. Thus, all three document analysis problems can be posed as texture segmentation problems. Two-dimensional Gabor filters are used to compute texture features. Both supervised and unsupervised methods are used to identify regions of text or bar code in the document images. The performance of the segmentation and classification scheme for a variety of document images demonstrates the generality and effectiveness of the approach. >