This work deals with the problem of recognition of Urdu characters using Fourier descriptors for optical networks. In particular, the scope of this work has been to develop a robust Urdu characters pattern classification, representation, and recognition system, which can classify patterns even if they are deformed by transformations like rotation, scaling, and translation or any combination of these, in the presence of noise. Fourier descriptors are used to uniquely describe, classify, and recognize Urdu characters within one sub-class, that provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. Although current information transmission media i.e. cable, Ethernet etc. may still be used for communications but we proposed new technology i.e. WDM (Wavelength Division Multiplexing) due to its high speed and low loss transmission. Finally experimental results are presented to show the power and robustness of the proposed technique for Urdu character recognition.
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.
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