Simple and effective techniques for skew correction, slant correction and core-region detection for cursive word recognition

Abstract

For the past decades, the advancement in the field of Image Processing has been paving a profound way in digital treatment of Human written data. Handwriting Recognition, a subset, is now a major research area to study as it is providing a mean for automatic processing of large volumes of data in reading and office automation. Intelligent word recognition systems which are used in processing important documents like bank cheques, old scripts are the need of the hour. Through this paper we present a new approach for Cursive word and Signature recognition. We propose Core-region detection technique which enables us to identify the crucial features of the hand written signatures by the extracting 'Ascenders and Descenders'. Skew and Slant corrections, if needed, are performed as preprocessing steps. A significant reduction in computation complexity has been observed than the previous attempts of researchers in detection of core-region. © 2012 Springer-Verlag GmbH Berlin Heidelberg.