A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Evaluation of Binarization Methods for Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handwriting Recognition
Gabor Feature Extraction for Character Recognition: Comparison with Gradient Feature
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Structural Decomposition and Statistical Description of Farsi/Arabic Handwritten Numeric Characters
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Classification Models for Historical Manuscript Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Arabic Handwriting Recognition Using Baseline Dependant Features and Hidden Markov Modeling
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian network classifier and hierarchical Gabor features for handwritten numeral recognition
Pattern Recognition Letters
Invariant Primitives for Handwritten Arabic Script: A Contrastive Study of Four Feature Sets
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
ICDAR 2009 Document Image Binarization Contest (DIBCO 2009)
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Gabor filters-based feature extraction for character recognition
Pattern Recognition
Arabic handwriting recognition using structural and syntactic pattern attributes
Pattern Recognition
Offline arabic handwritten text recognition: A Survey
ACM Computing Surveys (CSUR)
Texture feature evaluation for segmentation of historical document images
Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing
Multilingual OCR research and applications: an overview
Proceedings of the 4th International Workshop on Multilingual OCR
A comparison of machine learning techniques for handwritten |Xam word recognition
Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
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Many feature extraction approaches for off-line handwriting recognition (OHR) rely on accurate binarization of gray-level images. However, high-quality binarization of most real-world documents is extremely difficult due to varying characteristics of noises artifacts common in such documents. Unlike most of these features, Gabor features do not require binarization of the document images, and thus are likely to be more robust to noises in document images. To demonstrate the efficacy of our proposed Gabor features, we perform subword recognition for off-line Arabic handwritten images using Support Vector Machines (SVM). We also compare the recognition performance with other binarization based features which have been proven to be effective in capturing shape characteristics of handwritten Arabic subwords, such as GSC (a set of gradient, structure, and concavity features) and skeleton based Graph features. Our preliminary experimental results show that Gabor features outperform Graph features and are slightly better than GSC features for Arabic subword recognition. In addition, by combining Gabor and GSC features, we obtain a significant reduction in classification error rate over using GSC or Gabor features alone.