سال انتشار: ۱۳۸۵

محل انتشار: چهاردهمین کنفرانس مهندسی برق ایران

تعداد صفحات: ۴

نویسنده(ها):

Farhad Mohamad Kazemi – Islamic Azad University Mashad, IRAN
Hamid Reza Poorreza – Ferdowsi University Mashad, IRAN
Ali Akbari – Ferdowsi University Mashad, IRAN
Kambiz Rahbar – Islamic Azad University Mashad, IRAN

چکیده:

In this paper we study the recognition of contour-base hand written numeral characters using Multiwavelets and neural networks. For reaching this purpose, in the first step we extract numerals chain code by tracing their contours. Then we perform multiwavelet transform on it to prepare the appropriate features. Finally by employing the feed forward neural network we classify them into predefined classes. The neural network was trained with handwritten numeral database, MNIST. The experiments have demonstrated that the multiwavelet and neural network system is able
to more correct recognition of digits of the MNIST test set.