An Efficiently Computable Metric for Comparing Polygonal Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
A technique for computer detection and correction of spelling errors
Communications of the ACM
On Median Graphs: Properties, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Recognition of Handwritten Cursive Arabic Characters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonuniform Slant Correction Using Dynamic Programming
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-Uniform Slant Correction for Handwritten Text Line Recognition
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Arabic Handwriting Recognition Using Variable Duration HMM
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Lexicon reduction using dots for off-line Farsi/Arabic handwritten word recognition
Pattern Recognition Letters
Pattern Recognition Letters
Arabic handwritten digit recognition
International Journal on Document Analysis and Recognition
A Novel Connectionist System for Unconstrained Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Slanted-Frame Classifiers for Improved HMM-Based Arabic Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Segment Modeling for Offline Handwriting Recognition
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Improvements in BBN's HMM-Based Offline Arabic Handwriting Recognition System
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Arabic Handwriting Recognition Using Restored Stroke Chronology
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Off-line handwritten word recognition using multi-stream hidden Markov models
Pattern Recognition Letters
A novel template reduction approach for the K-nearest neighbor method
IEEE Transactions on Neural Networks
Graph embedding in vector spaces by means of prototype selection
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Gabor features for offline Arabic handwriting recognition
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Polygonal approximation of digital planar curves through adaptive optimizations
Pattern Recognition Letters
ICDAR 2011 - Arabic Handwriting Recognition Competition
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
Using diversity in classifier set selection for arabic handwritten recognition
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Offline arabic handwritten text recognition: A Survey
ACM Computing Surveys (CSUR)
Component retrieval based on a database of graphs for Hand-Written Electronic-Scheme Digitalisation
Expert Systems with Applications: An International Journal
KHATT: An open Arabic offline handwritten text database
Pattern Recognition
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In this paper, we present research results on off-line Arabic handwriting recognition using structural techniques. Statistical methods have been more common in the reported research on Arabic handwriting recognition. Structural methods have remained largely unexplored in this regard. However, both statistical and structural techniques can be effectively integrated in multi-classifier based systems. This paper presents, to our knowledge, the first integrated offline Arabic handwritten text recognition system based on structural techniques. In implementing the system, several novel algorithms and techniques for structural recognition of Arabic handwriting are introduced. An Arabic text line is segmented into words/sub-words and dots are extracted. An adaptive slant correction algorithm that is able to correct the different slant angles of the different components of a text line is presented. A novel segmentation algorithm, which is integrated into the recognition phase, is designed based on the nature of Arabic writing and utilizes a polygonal approximation algorithm. This is followed by Arabic character modeling by 'fuzzy' polygons and later recognized using a novel fuzzy polygon matching algorithm. Dynamic programming is used to select best hypotheses of a sequence of recognized characters for each word/sub-word. In addition, several other key ideas, namely prototype selection using set-medians, lexicon reduction using dot-descriptors etc. are utilized to design a robust handwriting recognition system. Results are reported on the benchmarking IfN/ENIT database of Tunisian city names which indicate the robustness and the effectiveness of our system. The recognition rates are comparable to multi-classifier implementations and better than single classifier systems.