A Method of Recognition of Arabic Cursive Handwriting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Chaincode Contour Processing for Handwritten Word Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Baseline Estimation For Arabic Handwritten Words
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Separation of Toching and Overlapping Words in Adjacent Lines of Handwritten Text
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lexicon reduction using dots for off-line Farsi/Arabic handwritten word recognition
Pattern Recognition Letters
Pattern Recognition Letters
Recognition of off-line printed Arabic text using Hidden Markov Models
Signal Processing
Region growing based segmentation algorithm for typewritten and handwritten text recognition
Applied Soft Computing
Handwritten Arabic text line segmentation using affinity propagation
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Offline arabic handwritten text recognition: A Survey
ACM Computing Surveys (CSUR)
The optical character recognition of Urdu-like cursive scripts
Pattern Recognition
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In order to improve the readability and the automatic recognition of handwritten document images, preprocessing steps are imperative. These steps in addition to conventional steps of noise removal and filtering include text normalization such as baseline correction, slant normalization and skew correction. These steps make the feature extraction process more reliable and effective. Recently Arabic handwriting recognition has received some attention from the research community. Due to the unique nature of the script, the conventional methods do not prove to be effective. In our work, we describe an orientation independent technique for baseline detection of Arabic words. In addition to that we describe, in the rest of the paper, our techniques for slant normalization, slope correction, line and word separation in handwritten Arabic documents. We show how the baseline can be exploited for slope and skew correction before proceeding with the steps of line and word separation.