Earticle

초록

영어

Compound characters which are one of the features of Marathi script, derived from Devanagari, occur frequently in the script. Recognition of these characters poses challenges to the researchers due to their complex structure. This paper presents a novel approach for recognition of unconstrained handwritten Marathi compound characters. The recognition is carried out using multistage feature extraction and classification scheme. The initial stages of feature extraction are based upon the structural features and the classification of the characters is done according to the structural parameters into 24 classes. The final stage of feature extraction employs wavelet transform. Single level wavelet decomposition is used to generate the approximation coefficients which are used as features. These coefficients are further modified and then used as another set of features. Both the wavelet approximation features as well as the modified wavelet features are applied to neural network for recognition. A separate neural network block is built for each of the 24 classes. The average recognition rate is found to be 96.14% and 94.22% respectively for training and testing samples with wavelet approximation features and 98.68% and 96.23% respectively for training and testing samples with modified wavelet features.

목차

Abstract
 1. Introduction
 2. Wavelet transform
 3. Neural networks
 4. The proposed scheme
  4.1. Data collection
  4.2. Pre-processing
  4.3. Structural classification
  4.4. Feature extraction
  4.5. Recognition
 5. Results and Discussion
 6. Conclusion
 References

키워드

저자

• Sushama Shelke [ Dept. of E & TC, Pune Institute of Computer Tech. ]
• Shaila Apte [ Dept. of E & TC, Pune Institute of Computer Tech. ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605