Font Recognition of English Letters Based on Distance Profile Features
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distance profile features, support vector machines, English font recognition, character font classification, optical font recognition
Abstract
This paper presents a system for recognizing English fonts from character images. The distance profile is the feature of choice used in this paper. The system extracts a vector of 106 features and feeds it into a support vector machine (SVM) classifier with a radial basis function (RBF) kernel. The experiment is divided into three phases. In the first phase, the system trains the SVM with different Gamma and C parameters. In the second phase, the validation phase, we validate and select the pair of Gamma and C values that yield the best recognition rates. In the final phase, the testing phase, the images are tested and the recognition rate is reported. Experimental results based on 27,620 characters glyph images from three English fonts show a 94.82% overall recognition rate.
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Copyright (c) 2020 Aveen J. Mohammed, Hasan S.M. Al-Khaffaf
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