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Inspired by the success of bag-of-words in text retrieval, bag-of-visual-words and its variants are widely used in content-based image retrieval to describe visual content. Various weighting schemes have also been proposed to integrate different yet complementary visual-words. However, most of these weighting schemes tend to use fixed weight for every visual-word extracted from the query image, which...
Digitizing printed document is always a challenge faced by the computing society. Digitization of text not only allows users to easily modify and reprint printed documents, but also is a need of the day due to the use of word-search capability available at disposal in this era. Converting a printed document into a stream of characters using OCR (optical character recognition) techniques is a widely...
State of art document segmentation algorithms employ adhoc solutions which use some document properties and iteratively segment the document image. These solutions need to be adapted frequently and sometimes fail to perform well for complex scripts. This calls for a generalized solution that achieves a one shot segmentation that is globally optimal. This paper describes one such solution based on...
We propose a full-text search technique for image-scanned documents that does not recognize individual characters. The system is as fast as a full-text search of machine-readable documents. Such a system is important when working with historical handwritten manuscripts. The proposed method works independently of differences in language and font because it uses a new pseudo-coding scheme based on the...
One of the major issues in document image processing is the efficient creation of ground truth in order to be used for training and evaluation purposes. Since a large number of tools have to be trained and evaluated in realistic circumstances, we need to have a quick and low cost way to create the corresponding ground truth. Moreover, the specific need for having the correct text correlated with the...
We present a method for figure caption detection by employing a fusion of several information sources. The evaluation is performed on documents gathered from the collection of the historical medical digital library Medic@. A method based on perceptual grouping simultaneously segments the vertical and horizontal text lines in a page. Spatial relationships between the text lines and the graphics are...
This paper examines the role of various linguistic structures on text classification applying the study to the Portuguese language. Besides using a bag-of-words representation where we evaluate different measures and use linguistic knowledge for term selection, we do several experiments using syntactic information representing documents as strings of words and strings of syntactic parse trees. To...
In this paper we consider the problem of unsupervised separation of mixed text patterns based on blind source separation models. We propose a hierarchical Markov random field model for the source patterns, which enforces piece-wise regularity on both labels and intensities of image pixels. We also presented a hierarchical Bayesian BSS framework, in which the unknown sources and labels is estimated...
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