Comparative study of feature extraction and classification methods for recognition of characters taken from vehicle registration plates

ABSTRACT

General Optical Character Recognition system works on the base of several successive steps such as pre-processing, segmentation, feature extraction, classification and post-processing. Feature extraction plays here a major role. In this article, we present an overview and comparison of various methods and approaches for off-line recognition of machine written Latin characters. We assume that individual characters are already segmented in an image. To recognize characters and translate them to text requires that each character must be described by a feature vector, which is then classified into one of the 36 classes corresponding to the uppercase Latin alphabet letters and numbers.