Extraction Method of Handwritten Digit Recognition Tested on the MNIST Database
B. El Kessab, Cherki Daoui, Belaid Bouikhalene, Mohamed Fakir, Kelmer Mozer Moro · International Journal of Advanced Science and Technology · 2013
This paper deals with an optical character recognition (OCR) system of handwritten digit, with the use of neural networks (MLP multilayer perceptron). And a method of extraction of characteristics based on the digit form, this method is tested on the MNIST handwritten isolated digit database (60000 images in learning and 10000 images in test). This work has achieved approximately 80% of success rate for MNIST database identification.