Shamsuddin, Siti Mariyam and Draman @ Muda, Azah Kamilah and Tan, Shuen Chuan (2006) Recognition of contour invariants with neurofuzzy classifier. Asian Journal of Information Technology, 5 (9). pp. 924-932.
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Abstract
In this study, we explore contour invariants for handwritten digits recognitions with neuro-fuzzy classifier. We use fuzzy triangular function in backpropagation network to initialize the weights. The results reveal that fuzzy triangular membership function manages to decrease the network convergence rate with proper parameter setting. In this study, unthinned images are appropriate for training and classification purpose as it preserves the images significant features. From our experiments, the results show that contour invariants exhibits highest rate of classification compares to geometric and zernike invariants.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Contour invariants, Geometric invariants, Zernike invariants, Neurofuzzy |
| Subjects: | Q Science > Q Science (General) |
| Divisions: | Faculty of Information and Communication Technology > Department of Software Engineeering |
| Depositing User: | Azah Kamilah Muda |
| Date Deposited: | 03 Aug 2011 03:38 |
| Last Modified: | 25 May 2023 12:18 |
| URI: | http://eprints.utem.edu.my/id/eprint/22 |
| Statistic Details: | View Download Statistic |
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