Chiang Mai Journal of Science, Faculty of Science, Chiang Mai University

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Paper Type	Opinion
Title	Digits Recognition with Moment Invariants
Author	Siti Mariyam Hj. Shamsuddin[a], Md. Nasir Sulaiman[a], and Maslina Darus[b]
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Abstract: This paper introduces an experimental evaluation of the utilizing various moments order as pattern features in recognition of handprinted and handwritten digits. The moments that have been used are Geometric moments and Aspect invariant moments. These moments have been used as feature extraction for digits with various orientations and scaling. We use standard backpropagation and an improved backpropagation for the classification of handprinted and handwritten digits for comparison. We found that the performance of handprinted and handwritten digits classifications are dependent on the moment order. Experiments on those digits using different moments order are carried out in classification phase, and the results are promising for moments of higher order.
Start & End Page	46 - 56
Received Date	1999-10-27
Revised Date
Accepted Date	2000-01-28
Full Text	Download
Keyword	moment invariants, digit recongnition, backpropagation, feature extraction
Volume	Vol.27 No.1 (JUNE 2000)
DOI
Citation	Shamsuddin S.M.H., Sulaiman M.N. and Darus M., Digits Recognition with Moment Invariants, Chiang Mai J. Sci., 2000; 27(1): 46-56.
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Activation Function of Sigmoid and Hyperbolic Tangent in Training Backpropagation Model - (A Comparison)
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Vol.27 No.1 (JUNE 2000) View: 590 Download:205

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