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12
Line Detection and Segmentation in Historical Church Registers
, 2001
"... For being able to automatically acquire the information recorded in church registers and other historical scriptures, the writing on these documents has to be recognized. This paper describes algorithms for transforming the paper documents into a representation of text apt to be used as input for an ..."
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Cited by 14 (2 self)
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For being able to automatically acquire the information recorded in church registers and other historical scriptures, the writing on these documents has to be recognized. This paper describes algorithms for transforming the paper documents into a representation of text apt to be used as input for an automatic text recognizer. The automatic recognition of old handwritten scriptures is difficult for two main reasons. Lines of text in general are not straight and ascenders and descenders of adjacent lines interfere. The algorithms described in this paper provide ways to reconstruct the path of the lines of text using an approach of gradually constructing line segments until an unique line of text is formed. In addition, the single lines are segmented and an output in form of a raster image is provided. The method was applied to church registers. They were written between the 17th and 19th century. Line segmentation was found to be successful in 97% of all samples.
Recognition and Verification of Unconstrained Handwritten Words
, 2005
"... This paper presents a novel approach for the verification of the word hypotheses generated by a large vocabulary, offline handwritten word recognition system. Given a word image, the recognition system produces a ranked list of the N-best recognition hypotheses consisting of text transcripts, segm ..."
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Cited by 8 (1 self)
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This paper presents a novel approach for the verification of the word hypotheses generated by a large vocabulary, offline handwritten word recognition system. Given a word image, the recognition system produces a ranked list of the N-best recognition hypotheses consisting of text transcripts, segmentation boundaries of the word hypotheses into characters, and recognition scores. The verification consists of an estimation of the probability of each segment representing a known class of character. Then, character probabilities are combined to produce word confidence scores which are further integrated with the recognition scores produced by the recognition system. The N-best recognition hypothesis list is reranked based on such composite scores. In the end, rejection rules are invoked to either accept the best recognition hypothesis of such a list or to reject the input word image. The use of the verification approach has improved the word recognition rate as well as the reliability of the recognition system, while not causing significant delays in the recognition process. Our approach is described in detail and the experimental results on a large database of unconstrained handwritten words extracted from postal envelopes are presented.
New Preprocessing techniques for handwritten word recognition
- Proceeding of the 2nd IASTED Conference on Visualization, Imaging and Image Processing
, 2002
"... The research described in this paper focuses on the presentation of two novel preprocessing techniques for the task of off-line handwritten word recognition. A technique for the identification of straight and skewed underline noise is described along with a novel algorithm for detecting skew in hand ..."
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Cited by 7 (0 self)
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The research described in this paper focuses on the presentation of two novel preprocessing techniques for the task of off-line handwritten word recognition. A technique for the identification of straight and skewed underline noise is described along with a novel algorithm for detecting skew in handwritten words. The latter identifies skew by detecting the center of mass in each half of a word image. By hypothesizing a line between the two centres and by measuring the angle it makes with the x-axis, an angle for skew may be estimated. The algorithms are tested on the CEDAR benchmark database of handwritten cursive words. Results above 96 % are reported for skew detection and underline removal.
Incorporating Contextual Character Geometry
- in Word Recognition,” Proc. Eighth Int’l Workshop Frontiers in Handwriting Recognition
, 2002
"... Contextual character geometry is the geometric information available only when a character presents in the context of a word. Such information includes a character’s location and relative size in the entire word image, forming a bounding box of the character. The differences between the geometry of ..."
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Cited by 3 (0 self)
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Contextual character geometry is the geometric information available only when a character presents in the context of a word. Such information includes a character’s location and relative size in the entire word image, forming a bounding box of the character. The differences between the geometry of an image segment and the expected geometry of a candidate character are considered as additional features to refine the recognition of individual characters. A typical word recognizer based on over-segmentation and segment-combination is used to illustrate the use of these new features and experimental results have shown significant improvement of recognition accuracy, especially on large lexicons. input image image segments Over-segmentation best alignment Dynamic Programming on segment combinations A m h e r s t
Robust Line Detection in Historical Church Registers
- In Pattern Recognition, 23rd DAGM Symposium
, 2001
"... For being able to automatically acquire information recorded in church registers and other historical scriptures, the text of such documents needs to be segmented prior to automatic reading. Segmentation of old handwritten scriptures is difficult for two main reasons. ..."
Abstract
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Cited by 1 (1 self)
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For being able to automatically acquire information recorded in church registers and other historical scriptures, the text of such documents needs to be segmented prior to automatic reading. Segmentation of old handwritten scriptures is difficult for two main reasons.
Discipline: Traitement du Signal et des Images
, 2009
"... HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
ACKNOWLEDGEMENTS
, 2009
"... « Reconnaissance de l’écriture manuscrite en-ligne par approche combinant systèmes à vastes marges et modèles de Markov cachés» ..."
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« Reconnaissance de l’écriture manuscrite en-ligne par approche combinant systèmes à vastes marges et modèles de Markov cachés»
Abstract NEW PREPROCESSING TECHNIQUES FOR HANDWRITTEN WORD RECOGNITION
"... The research described in this paper focuses on the presentation of two novel preprocessing techniques for the task of off-line handwritten word recognition. A technique for the identification of straight and skewed underline noise is described along with a novel algorithm for detecting skew in hand ..."
Abstract
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The research described in this paper focuses on the presentation of two novel preprocessing techniques for the task of off-line handwritten word recognition. A technique for the identification of straight and skewed underline noise is described along with a novel algorithm for detecting skew in handwritten words. The latter identifies skew by detecting the center of mass in each half of a word image. By hypothesizing a line between the two centres and by measuring the angle it makes with the x-axis, an angle for skew may be estimated. The algorithms are tested on the CEDAR benchmark database of handwritten cursive words. Results above 96 % are reported for skew detection and underline removal.
Abstract Recognition of Old Greek Early Christian
"... segmentation-free approach ..."
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Large Vocabulary Off-Line Handwritten Word Recognition
, 2002
"... Considerable progress has been made in handwriting recognition technology over the last few years. Thus far, handwriting recognition systems have been limited to small-scale and very constrained applications where the number of different words that a system can recognize is the key point for its per ..."
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Considerable progress has been made in handwriting recognition technology over the last few years. Thus far, handwriting recognition systems have been limited to small-scale and very constrained applications where the number of different words that a system can recognize is the key point for its performance. The capability of dealing with large vocabularies, however, opens up many more applications. In order to translate the gains made by research into large and very-large vocabulary handwriting recognition, it is necessary to further improve the computational effciency and the accuracy of the current recognition strategies and algorithms.
