Manjunath Aradhya, V. N. and Niranjan, S. K. and Hamsaveni, L. (2013) A robust analysis of FLD and orthogonal FLD on handwritten characters. In: Proceedings - 2013 International Conference on Communication Systems and Network Technologies, CSNT 2013.
Full text not available from this repository. (Request a copy)Abstract
Feature extraction is the identification of appropriate measures to characterize the component images distinctly. Extracting features is one of the most important steps in any recognition system. Hence, in this paper, we explore the concept of Orthogonalized Fisher Discriminant (OFD) for unconstrained handwritten Kannada character recognition. OFD exhibits higher performance than Fisher Linear Discriminant (FLD) due to the elimination of dependences among discriminant vectors. For subsequent classification purpose, we explore the concept of probabilistic neural network (PNN) architecture. Experiments show that OFD methods are more effective and efficient than standard FLD for handwritten character recognition.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Character recognition, Communication systems, Document image processing, Feature extraction, FLD, Hand written character recognition, Image processing, Neural networks, OFD, PNN |
| Subjects: | D Physical Science > Computer Science |
| Divisions: | Department of > Computer Science |
| Depositing User: | Arshiya Kousar Library Assistant |
| Date Deposited: | 22 Oct 2019 05:34 |
| Last Modified: | 22 Oct 2019 05:34 |
| URI: | http://eprints.uni-mysore.ac.in/id/eprint/9130 |
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