A Feature Based Chain Code Method for Identifying Printed Bengali Characters

نویسندگان

  • Ankita Sikdar
  • Payal Roy
  • Moumita Das
  • Sreeparna Banerjee
چکیده

This paper gives complete guidelines for authors submitting papers. This paper aims to explore a new way for recognizing printed Bengali characters. Keeping in mind, the possible shapes and orientations of the Bengali characters, we have developed a method to classify each of the 50 Bengali characters. An exhaustive study of the features of Bengali characters has been carried out which is presented in a hierarchical structure. The first few layers deal with features that broadly classify the characters into small size groups. The lower level features are more specific to each character within a group. While the higher level features can be identified based on pixel density and arrangement, the lower level features have been identified using chain code technique. The computer has been programmed to progress successively through each group in the hierarchy until it finds a match with the input character or rejects it.

برای دانلود رایگان 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

Topographic Feature Extraction for Bengali and Hindi Character Images

Feature selection and extraction plays an important role in different classification based problems such as face recognition, signature verification, optical character recognition (OCR) etc. The performance of OCR highly depends on the proper selection and extraction of feature set. In this paper, we present novel features based on the topography of a character as visible from different viewing...

متن کامل

An Analytic Scheme for Online Handwritten Bangla Cursive Word Recognition

In this article, we describe a prototype system for recognition of online handwritten cursive words of Bangla, a script used by more than 200 million people of India and Bangladesh, two neighboring countries of Asia. To the best of our knowledge, in the literature, there does not exist any work on recognition of such online Bangla cursive words. Here, we propose an analytic recognition approach...

متن کامل

Structural Run Based Feature Vector to Classify Printed Tamil Characters Using Neural Network

Feature Extraction plays most crucial and important role in character recognition. The selection of stable and representative set of features is the main problem in pattern recognition. Because of font characteristics and style variation of machine printed Tamil characters, feature extraction remains a problem. Feature extraction involves reducing the amount of resources required to describe a ...

متن کامل

Printed Arabic Characters Classification Using a Statistical Approach

In this paper, we propose simple classifiers for printed Arabic characters based on statistical analysis. 109 printed Arabic character images are created for each one of transparent, simplified and traditional Arabic fonts. Images are preprocessed by the binarization and followed by sequence of morphological operations. A non-linear filter is applied on the thinned ridge map to extract terminat...

متن کامل

A Medial Axis Based Thinning Strategy for Character Images

Thinning of character images is a big challenge. Removal of strokes or deformities in thinning is a difficult problem. In this paper, we have proposed a medial axis based thinning strategy used for performing skeletonization of printed and handwritten character images. In this method, we have used shape characteristics of text to get skeleton of nearly same as the true character shape. This app...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012