ICDAR 2009 Arabic Handwriting Recognition Competition

@article{Mrgner2009ICDAR2A,
  title={ICDAR 2009 Arabic Handwriting Recognition Competition},
  author={Volker M{\"a}rgner and Haikal El Abed},
  journal={2009 10th International Conference on Document Analysis and Recognition},
  year={2009},
  pages={1383-1387}
}
  • V. Märgner, H. E. Abed
  • Published 26 July 2009
  • Computer Science
  • 2009 10th International Conference on Document Analysis and Recognition
This paper describes the Online Arabic handwritingrecognition competition held at ICDAR 2009. This firstcompetition uses the ADAB-database with Arabic onlinehandwritten words. This year, 3 groups with 7 systems areparticipating in the competition. The systems were tested onknown data (sets 1 to 3) and on one test dataset which is unknownto all participants (set 4). The systems are comparedon the most important characteristic of classification systems,the recognition rate. Additionally, the… 

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References

SHOWING 1-10 OF 25 REFERENCES
Combining Slanted-Frame Classifiers for Improved HMM-Based Arabic Handwriting Recognition
TLDR
The results show that the combination of classifiers performs better than a single classifier dealing with slant-corrected images and that the approach is robust for a wide range of orientation angles.
Arabic Handwriting Recognition Using Restored Stroke Chronology
TLDR
This work uses a genetic algorithm to optimize the sequences of handwritten strokes and uses the beta-elliptical modelling which is developed in on-line systems to calculate other characteristics of the off-line handwriting recognition.
Combining Multiple HMMs Using On-line and Off-line Features for Off-line Arabic Handwriting Recognition
TLDR
This paper presents an off-line Arabic Handwriting recognition system based on the selection of different state of the art features and the combination of multiple Hidden Markov Models classifiers which exceeds the best result of the ICDAR 2005 competition.
Confidence-Based Discriminative Training for Model Adaptation in Offline Arabic Handwriting Recognition
  • P. Dreuw, G. Heigold, H. Ney
  • Computer Science
    2009 10th International Conference on Document Analysis and Recognition
  • 2009
We present a novel confidence-based discriminative training for model adaptation approach for an HMM based Arabic handwriting recognition system to handle different handwriting styles and their
ICDAR 2009 Handwriting Recognition Competition
  • E. Grosicki, H. E. Abed
  • Computer Science
    2009 10th International Conference on Document Analysis and Recognition
  • 2009
TLDR
This paper describes the handwriting recognition competition held at ICDAR 2009, based on the RIMES-database, with French written text documents, which shows interesting results.
ICDAR 2009 Online Arabic Handwriting Recognition Competition
TLDR
This paper describes the Online Arabic handwriting recognition competition held at ICDAR 2009, which uses the ADAB-database with Arabic online handwritten words and compares the systems on the most important characteristic of classification systems, the recognition rate.
Improvement of Arabic handwriting recognition systems; combination and/or reject?
TLDR
A comparison between two different combination schemes for the improvement of the performance of Arabic handwriting recognition systems based on fixed fusion using logical rules and trainable rules is presented.
Modified MMI/MPE: a direct evaluation of the margin in speech recognition
TLDR
This paper shows how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to incorporate a margin term, and shows that the proposed criteria are equivalent to Support Vector Machines with suitable smooth loss functions.
...
1
2
3
...