Publication Type:

Conference Paper

Source:

ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala (2009)

ISBN:

9780769538457

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-73849117418&partnerID=40&md5=0d5a3fafedfffe437baa7d1c87512eba

Keywords:

Connected component analysis, Existing method, Feature vectors, Font recognition, Gabor filter, Gears, Image retrieval, Local minimums, Multilayer neural networks, Novel techniques, Optical character recognition, Support vector machines, SVM classifiers, SVM model, Texture analysis, Vectors

Abstract:

Font Recognition is one of the Challenging tasks in Optical Character Recognition. Most of the existing methods for font recognition make use of local typographical features and connected component analysis. In this paper, English font recognition is done based on global texture analysis. The main objective of this proposal is to employ support vector machines (SVM) in identifying various fonts. The feature vectors are extracted by making use of Gabor filters and the proposed SVM is trained using these features. The method is found to give superior performance over neural networks by avoiding local minima points. The SVM model is formulated tested and the results are presented in this paper. It is observed that this method is content independent and the SVM classifier shows an average accuracy of 93.54%. © 2009 IEEE.

Cite this Research Publication

Dr. Ramanathan R., Thaneshwaran, L., Viknesh, V., Arunkumar, T., Yuvaraj, P., and Soman, K. P., “A novel technique for english font recognition using support vector machines”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.