Abstract
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
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