Paper
14 April 2000 Fuzzy-logic-model-based technique with application to Urdu character recognition
Dalila B. Megherbi, Saeed M. Lodhi, Azzoz J. Boulenouar
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Abstract
This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters based on concepts from Fuzzy logic. In particular, we show that Fuzzy logic is used here to make a classification of 36 Urdu characters into seven sub-classes namely sub-classes characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fuzzy logic provides a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of `interest regions' and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed Fuzzy logic based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dalila B. Megherbi, Saeed M. Lodhi, and Azzoz J. Boulenouar "Fuzzy-logic-model-based technique with application to Urdu character recognition", Proc. SPIE 3962, Applications of Artificial Neural Networks in Image Processing V, (14 April 2000); https://doi.org/10.1117/12.382911
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Fuzzy logic

Optical character recognition

Image filtering

Digital filtering

Image processing

Computing systems

Detection and tracking algorithms

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