Neural Network Based Approach for Recognition for Devanagiri Characters

نویسنده

  • Neha Sahu
چکیده

The development of a Character recognition system for Devnagri is difficult because (i) there are about 350 basic, modified (“matra”) and compound character shapes in the script and (ii) the characters in a words are topologically connected. Here focus is on the recognition of offline handwritten Hindi characters that can be used in common applications like bank cheques, commercial forms, government records, bill processing systems, Postcode Recognition, Signature Verification, passport readers, offline document recognition generated by the expanding technological society. Challenges in handwritten characters recognition lie in the variation and distortion of offline handwritten An approach using Artificial Neural Network is considered for recognition of Handwritten Hindi Character Recognition.

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

Neural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten

Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...

متن کامل

Online Handwriting Recognition of Gurmukhi and Devanagiri Characters in Mobile Phone Devices

This paper presents a system to recognize online handwritten Gurmukhi and Devanagiri characters in touch screen based mobile phones. We have used small line segments (derived from elastic matching and chain code techniques) to recognize Gurmukhi and Devanagiri characters. Mobile phones offer main challenges as: less memory and slow processer speed in comparison to Desktop or notebooks or Tablet...

متن کامل

Handwritten Character Recognition using Modified Gradient Descent Technique of Neural Networks and Representation of Conjugate Descent for Training Patterns

The purpose of this study is to analyze the performance of Back propagation algorithm with changing training patterns and the second momentum term in feed forward neural networks. This analysis is conducted on 250 different words of three small letters from the English alphabet. These words are presented to two vertical segmentation programs which are designed in MATLAB and based on portions (1...

متن کامل

Online Handwriting Recognition of Gurumukhi and Devanagiri Characters in Mobile Phone Devices

This paper presents a system to recognize online handwritten Gurmukhi and Devanagiri characters in touch screen based mobile phones. We have used small line segments (derived from elastic matching and chain code techniques) to recognize Gurmukhi and Devanagiri characters. Mobile phones offer main challenges as: less memory and slow processer speed in comparison to Desktop or notebooks or Tablet...

متن کامل

Pattern Recognition in Control Chart Using Neural Network based on a New Statistical Feature

Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...

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 2014