Earticle

초록

영어

Recognition of Handwritten text has been one of the active and challenging areas of research in the field of image processing and pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. In this paper we focus on recognition of English alphabet in a given scanned text document with the help of Neural Networks. Using Mat labNeural Network toolbox, we tried to recognize handwritten characters by projecting them on different sized grids. The first step is image acquisition which acquires the scanned image followed by noise filtering, smoothing and normalization of scanned image, rendering image suitable for segmentation where image is decomposed into sub images. Feature Extraction improves recognition rate and misclassification. We use character extraction and edge detection algorithm for training the neural network to classify and recognize the handwritten characters.

목차

Abstract
 1. Introduction
 2. The Proposed Model
  2.1 Image Acquisition
  2.2 Pre-Processing
  2.3 Segmentation
  2.4 Feature Extraction
  2.5 Classification and Recognition
  2.6 Post- processing
 3. Design And Implementation
 4. Algorithm Used
  4.1 Character Extraction Algorithm
  4.2 Edge Detection Algorithm
 5. Conclusion
 References

키워드

저자

• Kauleshwar Prasad [ B.I.T Durg ]
• Devvrat C. Nigam [ B.I.T Durg ]
• Ashmika Lakhotiya [ B.I.T Durg ]
• Dheeren Umre [ B.I.T Durg ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605