Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition

Details Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition

2010-06-30

arxiv.org/abs/1006.5902v1

IJCSI 2010

Computer Science

Computer Vision and Pattern Recognition

Scientific paper

Classification methods based on learning from examples have been widely applied to character recognition from the 1990s and have brought forth significant improvements of recognition accuracies. This class of methods includes statistical methods, artificial neural networks, support vector machines (SVM), multiple classifier combination, etc. In this paper, we discuss the characteristics of the some classification methods that have been successfully applied to handwritten Devnagari character recognition and results of SVM and ANNs classification method, applied on Handwritten Devnagari characters. After preprocessing the character image, we extracted shadow features, chain code histogram features, view based features and longest run features. These features are then fed to Neural classifier and in support vector machine for classification. In neural classifier, we explored three ways of combining decisions of four MLP's designed for four different features.

Affiliated with

Also associated with

No associations

Rating

Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-154327