V. M. O. Alves

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This paper describes an original method to segment handwritten text lines from historical document images. After an initial preprocessing, we compute a black/white transition map to achieve a rough detection of the line regions in the image. Using this map, the corresponding line axes are extracted through a skeletonization algorithm and the conflicts(More)
This paper presents a study on recognition of handwritten digits extracted from images of historical documents. The work is part of ProHist, a project aimed to make easier the diffusion of historical documents. Our objective herein is to recognize the dates written in the document for indexing purposes. In this paper we investigate the influence of the(More)
A novel method is proposed herein for handwritten digit segmentation in historical document images. It is based on one-class classifiers, which are used to distinguish isolated characters from touching characters. In contrast to other techniques based on feed forward neural networks, the proposed method does not require negative data in the training phase.(More)
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