Optical character recognition systems for Latin language

Abstract

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