Corpus ID: 17520563

Application of Support Vector Machines for Recognition of Handwritten Arabic/Persian Digits

@inproceedings{Sadri2003ApplicationOS,
  title={Application of Support Vector Machines for Recognition of Handwritten Arabic/Persian Digits},
  author={Javad Sadri and Ching Yee Suen and Tien D. Bui},
  year={2003}
}
A new method for recognition of isolated handwritten Arabic/Persian digits is presented. This method is based on Support Vector Machines (SVMs), and a new approach of feature extraction. Each digit is considered from four different views, and from each view 16 features are extracted and combined to obtain 64 features. Using these features, multiple SVM classifiers are trained to separate different classes of digits. CENPARMI Indian (Arabic/Persian) handwritten digit database is used for… Expand
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89 Citations
Highly Influential Citations
10
Background Citations
38
Methods Citations
30
Results Citations
2

89 Citations

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Citation Type

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TLDR
The presented technique, using simple features and SVM and ELM classifiers, are effective in the recognition of handwritten Arabic (Indian) numerals, and it is shown to be superior to HMM and NM classifiers for all digits. Expand
RECOGNITION OF OFF-LINE HANDWRITTEN ARABIC (INDIAN) NUMERALS USING MULTI-SCALE FEATURES AND SUPPORT VECTOR MACHINES VS. HIDDEN MARKOV MODELS
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The presented technique, using the powerful set of features and the SVM classifier, proved to be effective in the recognition of independent writer Arabic (Indian) numerals and was shown to be superior to the HMM classifier. Expand
Using Single-Layer neural network for recognition of isolated handwritten Persian digits
  • A. Pourmohammad, S. M. Ahadi
  • Computer Science
  • 2009 7th International Conference on Information, Communications and Signal Processing (ICICS)
  • 2009
TLDR
Experiments on real life samples from AMIRKABIR database showed that the proposed features, when used with SLP, could perform very well leading to a recognition rate of 98.3%, compared with 94.14% obtained from MLP classifier with SVM training using the CENPARMI database. Expand
Recognition of Arabic (Indian) bank check digits using log-gabor filters
TLDR
The experimental results, including the subjective evaluation of misclassified digits, indicate the effectiveness of the selected Log Gabor filters parameters, the implemented image segmentation technique, and extracted features for practical recognition of Arabic (Indian) digits. Expand
Arabic (Indian) handwritten digits recognition using Gabor-based features
  • S. Mahmoud
  • Computer Science
  • 2008 International Conference on Innovations in Information Technology
  • 2008
TLDR
The experimental results indicate the effectiveness of the Gabor-based features and SVM for Arabic (Indian) digits recognition. Expand
A New Decision Tree for Recognition of Persian Handwritten Characters
TLDR
A binary decision tree, based on Neural Networks, Support Vector Machine and K-Nearest Neighbor is employed and presented for recognition of Persian handwritten isolated digits and characters, where the tree leaves are the final obtained clusters. Expand
Off-line Recognition of Persian Handwritten Digits using Statistical Concepts
TLDR
In this paper is used the principal components analysis (PCA) to reduce dimension features set for recognition of Persian handwritten digits using central moments, Covariance, Median and Variance that are obtained at each the box digit image as the features set. Expand
Classifiers fusion method to recognize handwritten persian numerals
TLDR
A new approach for robust handwritten Persian numerals recognition using strong feature set and a classifier fusion method is scrutinized to increase the recognition percentage. Expand
Automatic Check Digits Recognition for Arabic Using Multi-Scale Features, HMM and SVM Classifiers
TLDR
Two Automatic Arabic (Indian) digits recognition systems using a real-life dataset of 3000 bank checks provides state-of-the-art recognition results on the CENPARMI database, as they reported a higher recognition rates when compared to twelve previously published systems, especially for the SVM system. Expand
Recognition of Handwritten Persian/Arabic Numerals Based on Robust Feature Set and K-NN Classifier
TLDR
A robust and efficient method for Persian/Arabic handwritten numerals recognition based on K Nearest Neighbors (K-NN) classifier is presented in this paper. Expand
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