Handwritten Gurmukhi Numeral Recognition using Zone-based Hybrid Feature Extraction Techniques

نویسندگان

  • Gita Sinha
  • Rajneesh Rani
  • Renu Dhir
  • Chih-Chung Chang
  • Rafael M. O. Cruz
  • George D. C. Cavalcanti
  • Tsang Ing Ren
  • L R Ragha
  • M Sasikumar
  • Xuewen Wang
  • Xiaoqing Ding
  • Arif Billah Al-Mahmud
  • Mahesh Jangid
  • Kartar Singh
  • Poulami Das
  • Suchandra Paul
  • Ranjit Ghoshal
  • Sushama Shelke
  • Shaila Apte
  • Shailedra Kumar Shrivastava
  • Sanjay S. Gharde
چکیده

This paper presents an overview of Feature Extraction techniques for off-line recognition of isolated Gurumukhi numerals/characters. Selection of Feature Extraction method is probably the single most important factor in achieving high performance in pattern recognition. Our paper presents Zone based hybrid approach which is the combination of image centroid zone and zone centroid zone of numeral/character image. In image centroid zone character is divided into n equal zone and then image centroid and the average distance from character centroid to each zones/grid/boxes present in image is calculated. Similarly, in zone centroid zone character image is divided into n equal zones and centroid of each zones/boxes/grid and average distance from zone centroid to each pixel present in block/zone/grid is calculated. SVM for subsequent classifier and recognition purpose. Obtaining 99. 73% recognition accuracy.

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

Zone-Based Feature Extraction Techniques and SVM for Handwritten Gurmukhi Character Recognition

In this paper we present an overview of Feature Extraction techniques for off-line recognition of isolated Gurumukhi characters recognition. Selection of Feature Extraction method is probably the single most important factor in achieving high performance in pattern recognition. Our paper presents Zone based approach which is the combination of image centroid zone and zone centroid zone of numer...

متن کامل

Zone Based Feature Extraction Techniques For Bangla Numerals Recognition

This paper proposed a methodology for Handwritten Bangla numerals Recognition using zone based Feature Extraction Techniques. Every numeral image is pre-processed, segmented and feature are Extracted from each zone. In this paper we present, three zone based feature extraction techniques which is namely: image Centroid zone(ICZ), zone centroid zone (ZCZ) and hybrid feature extraction techniques...

متن کامل

SVM Based Offline Handwritten Gurmukhi Character Recognition

Support Vector Machines (SVMs) have successfully been used in recognizing printed characters. In the present work, we have used this classification technique to recognize handwritten characters. Recognition of handwritten characters is a difficult task owing to various writing styles of individuals. A scheme for offline handwritten Gurmukhi character recognition based on SVMs is presented in th...

متن کامل

Handwritten Gurumukhi Character Recognition Using Convolution Neural Network

Handwritten Character Recognition (HCR) is one of the challenging processes. Automatic recognition of handwritten characters is a difficult task. In this paper, we have presented a scheme for offline handwritten Gurmukhi character recognition based on CNN classifier. The system first prepares a skeleton of the character, so that feature information about the character is extracted. CNN based ap...

متن کامل

Feature Extraction and Classification Techniques in O.C.R. Systems for Handwritten Gurmukhi Script – A Survey

Optical character recognition (OCR) is very popular research field since 1950’s. A great work has been done for various scripts particularly in case of English. But in case of Indian scripts the research is limited. This paper presents an overview of the various O.C.R. systems for gurmukhi which are developed for handwritten isolated gurmukhi text. In case of printed gurmukhi text a lot of rese...

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 2012