FPGA-Based Farsi Handwritten Digit Recognition System

نویسندگان

  • Marzieh Moradi
  • Mohammad Ali Pourmina
  • Farbod Razzazi
چکیده

A new method for feature extraction based on FPGA (Field Programmable Gate Arrays) implementation is proposed in this paper. The specific application is offline Farsi handwritten digit recognition. The classification is based on a simple two layer MLP (Multi Layer Perceptron). This method of feature extraction is appropriate for FPGA implementation as it can be implemented only with addition and subtraction operations. The proposed method is used to extract the features from normalized 40×40 pixel handwritten digit images from Standard Hoda database. Exprimentally results showed that the proposed system achived about 96% accuracy. Overally the system is simple, more accurate and less complex than the other similar systems.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Persian Handwritten Digit Recognition Using Particle Swarm Probabilistic Neural Network

Handwritten digit recognition can be categorized as a classification problem. Probabilistic Neural Network (PNN) is one of the most effective and useful classifiers, which works based on Bayesian rule. In this paper, in order to recognize Persian (Farsi) handwritten digit recognition, a combination of intelligent clustering method and PNN has been utilized. Hoda database, which includes 80000 P...

متن کامل

Challenges of Handwriting Recognition in Farsi , Arabic and Other Languages with Similar Writing StylesAn On - line Digit

This paper will emphasize the necessity of having alternative man-machine interfaces to the already established keyboard and mouse, speciically for people residing in developing countries. An on-line system is presented for recognizing handwritten Farsi (Persian) and Arabic digits. This recognition scheme is based on statistical techniques which will be brieey explained. Then, the grounds will ...

متن کامل

Hand Written Digit Recognition by Multiple Classifier Fusion based on Decision Templates Approach

Classifier fusion may generate more accurate classification than each of the basic classifiers. Fusion is often based on fixed combination rules like the product, average etc. This paper presents decision templates as classifier fusion method for the recognition of the handwritten English and Farsi numerals (1-9). The process involves extracting a feature vector on well-known image databases. T...

متن کامل

A Hybrid Structural/Statistical Classifier for Handwritten Farsi/Arabic Numeral Recognition

In this paper a new Farsi/Arabic numeral recognition system, based on the combination of structural and statistical classifiers, is presented. The structural method cannot deal with broken characters well. A statistical classifier would be more suitable for these unconnected samples. Thanks to the combination of structural and statistical approaches, a complete description of the characters can...

متن کامل

Persian Handwritten Digit Recognition Using Particle Swarm Probabilistic Neural Network

Handwritten digit recognition can be categorized as a classification problem. Probabilistic Neural Network (PNN) is one of the most effective and useful classifiers, which works based on Bayesian rule. In this paper, in order to recognize Persian (Farsi) handwritten digit recognition, a combination of intelligent clustering method and PNN has been utilized. Hoda database, which includes 80000 P...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011