Digits Recognition with Moment Invariants
Siti Mariyam Hj. Shamsuddin[a], Md. Nasir Sulaiman[a], and Maslina Darus[b]* Author for corresponding; e-mail address: -
Volume: Vol.27 No.1 (JUNE 2000)
Opinion
DOI:
Received: 27 October 1999, Revised: -, Accepted: 28 January 2000, Published: -
Citation: Shamsuddin S.M.H., Sulaiman M.N. and Darus M., Digits Recognition with Moment Invariants, Chiang Mai Journal of Science, 2000; 27(1): 46-56.
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.