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Assabie, Yaregal
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Publications (10 of 15) Show all publications
Assabie, Y. & Bigun, J. (2011). Offline handwritten Amharic word recognition. Pattern Recognition Letters, 32(8), 1089-1099
Open this publication in new window or tab >>Offline handwritten Amharic word recognition
2011 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 32, no 8, p. 1089-1099Article in journal (Refereed) Published
Abstract [en]

This paper describes two approaches for Amharic word recognition in unconstrained handwritten text using HMMs. The first approach builds word models from concatenated features of constituent characters and in the second method HMMs of constituent characters are concatenated to form word model. In both cases, the features used for training and recognition are a set of primitive strokes and their spatial relationships. The recognition system does not require segmentation of characters but requires text line detection and extraction of structural features, which is done by making use of direction field tensor. The performance of the recognition system is tested by a dataset of unconstrained handwritten documents collected from various sources, and promising results are obtained. (C) 2011 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2011
Keywords
Amharic, Ethiopic script, Handwriting recognition, Word recognition, OCR, HMM
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-14949 (URN)10.1016/j.patrec.2011.02.007 (DOI)000290745100002 ()2-s2.0-79953057096 (Scopus ID)
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2018-03-23Bibliographically approved
Assabie, Y. & Bigun, J. (2009). A comprehensive Dataset for Ethiopic Handwriting Recognition. In: Josef Bigun & Antanas Verikas (Ed.), Proceedings SSBA '09: Symposium on Image Analysis, Halmstad University, Halmstad, March 18-20, 2009 (pp. 41-43). Halmstad: Halmstad University
Open this publication in new window or tab >>A comprehensive Dataset for Ethiopic Handwriting Recognition
2009 (English)In: Proceedings SSBA '09: Symposium on Image Analysis, Halmstad University, Halmstad, March 18-20, 2009 / [ed] Josef Bigun & Antanas Verikas, Halmstad: Halmstad University , 2009, p. 41-43Chapter in book (Other academic)
Abstract [en]

Ethiopic script is used by several languages in Ethiopia for writing. We present a comprehensive dataset of handwritten Ethiopic script called DEHR (Dataset for Ethiopic Handwriting Recognition) captured both offline and online. The offline dataset includes isolated characters, Ethiopian church documents and ordinary handwritten texts dealing with various real-life issues. The ordinary texts and isolated characters were freely written by several participants. The church documents are written in Geez and Amharic languages whereas the language for ordinary texts is Amharic only. The online dataset was collected by using two Digimemo devices of different sizes. For isolated characters and online dataset, all the 265 character samples used by Amharic language are included. The dataset is intended to set a benchmark for training and/or testing handwriting recognition, character and word segmentation, and text line detection. The dataset is can be accessed by contacting the authors or via http://www.hh.se/staff/josef/.

Place, publisher, year, edition, pages
Halmstad: Halmstad University, 2009
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:hh:diva-25833 (URN)978-91-633-3924-0 (ISBN)
Available from: 2014-06-24 Created: 2014-06-24 Last updated: 2018-03-22Bibliographically approved
Assabie, Y. & Bigun, J. (2009). HMM-Based Handwritten Amharic Word Recognition with Feature Concatenation. In: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR: . Paper presented at 10th International Conference on Document Analysis and Recognition, ICDAR '09, July 26-29, Barcelona, Spain, 2009 (pp. 961-965). New York: IEEE Press
Open this publication in new window or tab >>HMM-Based Handwritten Amharic Word Recognition with Feature Concatenation
2009 (English)In: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, New York: IEEE Press, 2009, p. 961-965Conference paper, Published paper (Refereed)
Abstract [en]

Amharic is the official language of Ethiopia and uses Ethiopic script for writing. In this paper, we present writer-independent HMM-based Amharic word recognition for offline handwritten text. The underlying units of the recognition system are a set of primitive strokes whose combinations form handwritten Ethiopic characters. For each character, possibly occurring sequences of primitive strokes and their spatial relationships, collectively termed as primitive structural features, are stored as feature list. Hidden Markov models for Amharic words are trained with such sequences of structural features of characters constituting words. The recognition phase does not require segmentation of characters but only requires text line detection and extraction of structural features in each text line. Text lines and primitive structural features are extracted by making use of direction field tensor. The performance of the recognition system is tested by a database of unconstrained handwritten documents collected from various sources.

Place, publisher, year, edition, pages
New York: IEEE Press, 2009
Series
International Conference on Document Analysis and Recognition, ICDAR, ISSN 1520-5363 ; Article number 5277562
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-14940 (URN)10.1109/ICDAR.2009.50 (DOI)2-s2.0-71249083101 (Scopus ID)
Conference
10th International Conference on Document Analysis and Recognition, ICDAR '09, July 26-29, Barcelona, Spain, 2009
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2018-03-23Bibliographically approved
Assabie, Y. & Bigun, J. (2009). Offline Handwritten Amharic Word Recognition Using HMMs. In: Josef Bigun & Antanas Verikas (Ed.), Proceedings SSBA '09: Symposium on Image Analysis, Halmstad University, Halmstad, March 18-20, 2009 (pp. 89-92). Halmstad: Halmstad University
Open this publication in new window or tab >>Offline Handwritten Amharic Word Recognition Using HMMs
2009 (English)In: Proceedings SSBA '09: Symposium on Image Analysis, Halmstad University, Halmstad, March 18-20, 2009 / [ed] Josef Bigun & Antanas Verikas, Halmstad: Halmstad University , 2009, p. 89-92Chapter in book (Other academic)
Abstract [en]

This paper describes two appraches for Amharic word recognition in unconstrained handwritten text using HMMs. The first approach builds word models from concatenated features of constituent characters and in the second method HMMs of constituent characters are concatenated to form word model. In both cases, the features used for training and recognition are primitive strokes and their spatial relationships. The recognition system does not require segmentation of characters but requires text line detection and extraction of structural features, which is done by making use of direction field tensor. The performance of the recognition system is tested by DEHR dataset of unconstrained handwritten documents collected from various sources.

Place, publisher, year, edition, pages
Halmstad: Halmstad University, 2009
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:hh:diva-25837 (URN)978-91-633-3924-0 (ISBN)
Available from: 2014-06-24 Created: 2014-06-24 Last updated: 2018-03-22Bibliographically approved
Assabie, Y. & Bigun, J. (2008). Lexicon-based Offline Recognition of Amharic Words in Unconstrained Handwritten Text. In: 19th International Conference on Pattern Recognition: (ICPR 2008) ; Tampa, Florida, USA 8-11 December 2008. Paper presented at 19th International Conference on Pattern Recognition, ICPR, Tampa, FL, 8-11 December 2008. New York: IEEE Computer Society, Article ID 4761145.
Open this publication in new window or tab >>Lexicon-based Offline Recognition of Amharic Words in Unconstrained Handwritten Text
2008 (English)In: 19th International Conference on Pattern Recognition: (ICPR 2008) ; Tampa, Florida, USA 8-11 December 2008, New York: IEEE Computer Society, 2008, article id 4761145Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes an offline handwriting recognition system for Amharic words based on lexicon. The system computes direction fields of scanned handwritten documents, from which pseudo-characters are segmented. The pseudo-characters are organized based on their proximity and direction to form text lines. Words are then segmented by analyzing the relative gap between subsequent pseudocharacters in text lines. For each segmented word image, the structural characteristics of pseudo-characters are syntactically analyzed to predict a set of plausible characters forming the word. The most likelihood word is finally selected among candidates by matching against the lexicon. The system is tested by a database of unconstrained handwritten Amharic documents collected from various sources. The lexicon is prepared from words appearing in the collected database.

Place, publisher, year, edition, pages
New York: IEEE Computer Society, 2008
Series
International Conference on Pattern Recognition, ISSN 1051-4651 ; 19
National Category
Computer Sciences
Identifiers
urn:nbn:se:hh:diva-14936 (URN)000264729001263 ()2-s2.0-77957937455 (Scopus ID)978-1-4244-2174-9 (ISBN)
Conference
19th International Conference on Pattern Recognition, ICPR, Tampa, FL, 8-11 December 2008
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2018-03-23Bibliographically approved
Assabie, Y. & Bigun, J. (2008). Online Handwriting Recognition of Ethiopic Script. In: Ching Y Suen (Ed.), Proceedings: Eleventh International Conference on Frontiers in Handwriting Recognition, Montréal, Québec - Canada, August 19-21, 2008. Paper presented at Eleventh International Conference on Frontiers in Handwriting Recognition (ICFHR2008), August 19-21, Montreal, Quebec, Canada (pp. 153-158). Montréal: CENPARMI, Concordia University
Open this publication in new window or tab >>Online Handwriting Recognition of Ethiopic Script
2008 (English)In: Proceedings: Eleventh International Conference on Frontiers in Handwriting Recognition, Montréal, Québec - Canada, August 19-21, 2008 / [ed] Ching Y Suen, Montréal: CENPARMI, Concordia University , 2008, p. 153-158Conference paper, Published paper (Refereed)
Abstract [en]

Online recognition of handwritten characters is gaining a renewed interest as it provides a natural way of data entry for a wide variety of handheld devices. In this paper, we present online handwriting recognition system for Ethiopic script based on the structural and syntactical analysis of the strokes forming characters. The complex structures of characters are represented by the spatio- temporal relationships of simple-shaped strokes called primitives. A special tree structure is used to model spatio- temporal relationships of the strokes. The tree generates a unique set of primitive stroke sequences for each character, and for recognition each stroke sequence is matched against a stored knowledge base. Characters are also classified based on their structural similarity to select a plausible set of characters for un unknown input, which improves recognition and processing time. We also present a dataset collected for training and testing online recognition systems for Ethiopic script. The dataset is prepared in accordance with the international standard UNIPEN format. The recognition system is tested with the collected dataset and experimental results are reported.

Place, publisher, year, edition, pages
Montréal: CENPARMI, Concordia University, 2008
Keywords
Ethiopic, Handwritten, Online Recognition
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-14935 (URN)1895193036 (ISBN)9781895193039 (ISBN)
Conference
Eleventh International Conference on Frontiers in Handwriting Recognition (ICFHR2008), August 19-21, Montreal, Quebec, Canada
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2018-03-23Bibliographically approved
Assabie, Y. & Bigun, J. (2008). Writer-independent Offline Recognition of Handwritten Ethiopic Characters. In: Ching Y Suen (Ed.), Proceedings: Eleventh International Conference on Frontiers in Handwriting Recognition, Montréal, Québec - Canada, August 19-21, 2008. Paper presented at Eleventh International Conference on Frontiers in Handwriting Recognition (ICFHR2008), August 19-21, Montreal, Quebec, Canada (pp. 652-657). Montréal: CENPARMI, Concordia University
Open this publication in new window or tab >>Writer-independent Offline Recognition of Handwritten Ethiopic Characters
2008 (English)In: Proceedings: Eleventh International Conference on Frontiers in Handwriting Recognition, Montréal, Québec - Canada, August 19-21, 2008 / [ed] Ching Y Suen, Montréal: CENPARMI, Concordia University , 2008, p. 652-657Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents writer-independent offline handwritten character recognition for Ethiopic script. The recognition is based on the characteristics of primitive strokes that make up characters. The spatial relationships of primitives whose combinations form complex structures of Ethiopic characters are used as a basis for recognition. Although this approach efficiently recognizes properly written characters, the recognition rate drops for characters where the spatial relationships of their primitives could not be drawn. This happens mostly when the connections between primitives are not properly written, which is a common case in handwriting. To complement the recognition, we classify characters based on the characteristics of their primitives, resulting in grouping of characters in a five-dimensional space. Once the type of characters is identified, recognition can be achieved with a minimal set of information from their spatial relationships. A comprehensive database is also developed to standardize the evaluation of research works on offline Ethiopic handwriting recognition systems. Our proposed system is tested is with the database and experimental results are reported.

Place, publisher, year, edition, pages
Montréal: CENPARMI, Concordia University, 2008
Keywords
Ethiopic, Handwriting Recognition, Database
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-14934 (URN)1895193036 (ISBN)9781895193039 (ISBN)
Conference
Eleventh International Conference on Frontiers in Handwriting Recognition (ICFHR2008), August 19-21, Montreal, Quebec, Canada
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2018-03-23Bibliographically approved
Assabie, Y. & Bigun, J. (2007). A Hybrid System for Robust Recognition of Ethiopic Script. In: IEEE Computer Society (Ed.), Ninth International Conference on Document Analysis and Recognition: proceedings : Curtiba, Paraná, Brazil, September 23-26, 2007. Paper presented at Ninth International Conference on Document Analysis and Recognition, Curtiba, Paraná, Brazil, September 23-26, 2007 (pp. 556-560). Los Alamitos, Calif.: IEEE Computer Society
Open this publication in new window or tab >>A Hybrid System for Robust Recognition of Ethiopic Script
2007 (English)In: Ninth International Conference on Document Analysis and Recognition: proceedings : Curtiba, Paraná, Brazil, September 23-26, 2007 / [ed] IEEE Computer Society, Los Alamitos, Calif.: IEEE Computer Society, 2007, p. 556-560Conference paper, Published paper (Refereed)
Abstract [en]

In real life, documents contain several font types, styles, and sizes. However, many character recognition systems show good results for specific type of documents and fail to produce satisfactory results for others. Over the past decades, various pattern recognition techniques have been applied with the aim to develop recognition systems insensitive to variations in the characteristics of documents. In this paper, we present a robust recognition system for Ethiopic script using a hybrid of classifiers. The complex structures of Ethiopic characters are structurally and syntactically analyzed, and represented as a pattern of simpler graphical units called primitives. The pattern is used for classification of characters using similarity-based matching and neural network classifier. The classification result is further refined by using template matching. A pair of directional filters is used for creating templates and extracting structural features. The recognition system is tested by real life documents and experimental results are reported.

Place, publisher, year, edition, pages
Los Alamitos, Calif.: IEEE Computer Society, 2007
Keywords
character recognition, character sets, document image processing, feature extraction, iltering theory, image classification, image matching, natural language processing, neural nets
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-2151 (URN)10.1109/ICDAR.2007.4378771 (DOI)000252162600112 ()2-s2.0-51149094370 (Scopus ID)2082/2546 (Local ID)978-0-7695-2822-9 (ISBN)2082/2546 (Archive number)2082/2546 (OAI)
Conference
Ninth International Conference on Document Analysis and Recognition, Curtiba, Paraná, Brazil, September 23-26, 2007
Note

©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Available from: 2008-11-20 Created: 2008-11-20 Last updated: 2018-03-23Bibliographically approved
Assabie, Y. & Bigun, J. (2007). A neural network approach for multifont and size-independent recognition of ethiopic characters. In: Singh, S, Singh, M (Ed.), Progress in pattern recognition. Paper presented at International Workshop on Advances in Pattern Recognition (IWAPR), Loughborough Univ, Loughborough, England, 2007 (pp. 129-137). Springer London
Open this publication in new window or tab >>A neural network approach for multifont and size-independent recognition of ethiopic characters
2007 (English)In: Progress in pattern recognition / [ed] Singh, S, Singh, M, Springer London, 2007, p. 129-137Conference paper, Published paper (Refereed)
Abstract [en]

Artificial neural networks are one of the most commonly used tools for character recognition problems, and usually they take gray values of 2D character images as inputs. In this paper, we propose a novel neural network classifier whose input is ID string patterns generated from the spatial relationships of primitive structures of Ethiopiccharacters. The spatial relationships of primitives are modeled by a special tree structure from which a unique set of string patterns are generated for each character. Training theneural network with string patterns of different font types and styles enables the classifier to handle variations in font types, sizes, and styles. We use a pair of directional filters forextracting primitives and their spatial relationships. The robustness of the proposed recognition system is tested by real life documents and experimental results are reported.

Place, publisher, year, edition, pages
Springer London, 2007
Series
Advances in Pattern Recognition, ISSN 1617-7916
Keywords
Image analysis, Ethiopic characters, Pattern recognition
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-2159 (URN)10.1007/978-1-84628-945-3_13 (DOI)000250406000013 ()2082/2554 (Local ID)978-1-84628-944-6 (ISBN)2082/2554 (Archive number)2082/2554 (OAI)
Conference
International Workshop on Advances in Pattern Recognition (IWAPR), Loughborough Univ, Loughborough, England, 2007
Available from: 2008-11-24 Created: 2008-11-24 Last updated: 2018-03-23Bibliographically approved
Assabie, Y. & Bigun, J. (2007). Multifont size-resilient recognition system for Ethiopic script. International Journal on Document Analysis and Recognition, 10(2), 85-100
Open this publication in new window or tab >>Multifont size-resilient recognition system for Ethiopic script
2007 (English)In: International Journal on Document Analysis and Recognition, ISSN 1433-2833, E-ISSN 1433-2825, Vol. 10, no 2, p. 85-100Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel framework for recognition of Ethiopic characters using structural and syntactic techniques. Graphically complex characters are represented by the spatial relationships of less complex primitives which form a unique set of patterns for each character. The spatial relationship is represented by a special tree structure which is also used to generate string patterns of primitives. Recognition is then achieved by matching the generated string pattern against each pattern in the alphabet knowledge-base built for this purpose. The recognition system tolerates variations on the parameters of characters like font type, size and style. Direction field tensor is used as a tool to extract structural features.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2007
Keywords
Direction field tensor, Ethiopic, Multifont, Optical character recognition, Structural and syntactic techniques
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hh:diva-1360 (URN)10.1007/s10032-007-0048-y (DOI)000251379500004 ()2-s2.0-36349008568 (Scopus ID)2082/1739 (Local ID)2082/1739 (Archive number)2082/1739 (OAI)
Available from: 2008-04-25 Created: 2008-04-25 Last updated: 2018-03-23Bibliographically approved
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