  Text segmentation is an inherent part of an OCR system irrespective of the
domain of application of it. The OCR system contains a segmentation module
where the text lines, words and ultimately the characters must be segmented
properly for its successful recognition. The present work implements a Hough
transform based technique for line and word segmentation from digitized images.
The proposed technique is applied not only on the document image dataset but
also on dataset for business card reader system and license plate recognition
system. For standardization of the performance of the system the technique is
also applied on public domain dataset published in the website by CMATER,
Jadavpur University. The document images consist of multi-script printed and
hand written text lines with variety in script and line spacing in single
document image. The technique performs quite satisfactorily when applied on
mobile camera captured business card images with low resolution. The usefulness
of the technique is verified by applying it in a commercial project for
localization of license plate of vehicles from surveillance camera images by
the process of segmentation itself. The accuracy of the technique for word
segmentation, as verified experimentally, is 85.7% for document images, 94.6%
for business card images and 88% for surveillance camera images.
