Abstract
The paper proposes automatic segmentation of handwritten document binary images. The Hough transform (HT) over the source image is applied and then the slope of handwritten rows is estimated by analyzing the parameter plane. The inverse HT is used for ‘cutting’ the image and forming ‘strips’, containing the respective handwritten rows. Localization of words is a result of convolution with a proper mask. Such segmentation aims at extracting the specific features of handwriting.
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