Optical character recognition systems for English language

Abstract

The optical character recognition (OCR) systems for English language were the most primitive ones and occupy a significant place in pattern recognition. The English language OCR systems have been used successfully in a wide array of commercial applications. The different challenges involved in the OCR systems for English language is investigated in this chapter. The pre-processing activities such as binarization, noise removal, skew detection and correction, character segmentation and thinning are performed on the datasets considered. The feature extraction is performed through discrete cosine transformation. The feature based classification is performed through important soft computing techniques viz fuzzy multilayer perceptron (FMLP), rough fuzzy multilayer perceptron (RFMLP), fuzzy support vector machine (FSVM) and fuzzy rough support vector machine (FRSVM). The superiority of soft computing techniques is demonstrated through the experimental results.