Title :
A Novel Technique for English Font Recognition Using Support Vector Machines
Author :
Ramanathan, R. ; Soman, K.P. ; Thaneshwaran, L. ; Viknesh, V. ; Arunkumar, T. ; Yuvaraj, P.
Author_Institution :
Dept. of Electron. & Commun. Eng., Amrita Vishwa Vidyapeetham, Coimbatore, India
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%.
Keywords :
character sets; feature extraction; optical character recognition; support vector machines; English font recognition; Gabor filters; SVM classifier; SVM model; feature vector extraction; global texture analysis; neural networks; optical character recognition; support vector machines; Character recognition; Feature extraction; Gabor filters; Neural networks; Optical character recognition software; Optical filters; Proposals; Support vector machine classification; Support vector machines; Testing; English font recognition; Gabor filter; Optical Character Recognition; Support vector machine;
Conference_Titel :
Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on
Conference_Location :
Kottayam, Kerala
Print_ISBN :
978-1-4244-5104-3
Electronic_ISBN :
978-0-7695-3845-7
DOI :
10.1109/ARTCom.2009.89
