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An ongoing considerable effort for digitizing historical manuscripts has produced images of original manuscripts, some accompanied by transcripts. Aligning the text in the input image with the text in the transcript will allow learning, training and evaluating recognition algorithms. Here we propose a system that computes the alignment by formulating the problem as an energy minimization task, where...
Many applications along the manuscript analysis pipeline rely on the accuracy of pre-processing steps. Perfectly detecting the main text area in ancient historical documents is of great importance for these applications. We propose a learning-free approach to detect the main text area in ancient manuscripts. First, we coarsely segment the main text area by using a texture-based filter. Then, we refine...
Most of the algorithms proposed for text line detection are designed to process binary images as input. For severely degraded documents, binarization often introduces significant noise and other artifacts. In this work we present a novel method designed to detect text lines directly in gray scale images. The method consists of two stages. Potential characters are detected in the first stage. This...
We present WebGT, the first web-based system to help users produce ground truth data for document images. This user-friendly software system helps historians and computer scientists collectively annotate historical documents. It supports real time collaboration among remote sites independent of the local operating system and also provides several novel semi-automatic tools that have proven effective...
For highly degraded text documents, common tasks such as binarization and line extraction, remain difficult tasks. Equipped with a reliable information regarding the distribution of character dimensions in the document, one can improve results of these algorithms significantly. We introduce a novel perspective of the image data which maps the evolution of connected components along the change in gray...
Broken or partially visible characters is common phenomenon in historical documents. It stems from various factors, such as overlaid text or degradation. Restoring such characters is necessary for document analysis applications. This paper presents a new approach for restoring underlaying Hebrew broken characters that were partially occluded by Arabic text in a palimpsest. We apply text recognition...
Searching for a letter or a word in historical documents is a practical challenge due to the various degradations present in such documents and the wide variance of handwriting. Searching in historical Hebrew documents is somewhat harder because of high similarities among Hebrew characters. In order to determine the features and their combinations appropriate for recognizing Hebrew script, we study...
We propose a variational method for model based segmentation of gray-scale images of highly degraded historical documents. Given a training set of characters (of a certain letter), we construct a small set of shape models that cover most of the training set's shape variance. For each gray-scale image of a respective degraded character, we construct a custom made shape prior using those fragments of...
We present our work on the paleographic analysis and recognition system intended for processing of historical Hebrew calligraphy documents. The main goal is to analyze documents of different writing styles in order to identify the locations, dates, and writers of test documents. Using interactive software tools, a data base of extracted characters has been established. It now contains about 20,000...
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