CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 1999 vol.21 Issue No.08 - August
Issue No.08 - August (1999 vol.21)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.784289
<p><b>Abstract</b>—In this paper, we propose a new class of histogram based global thresholding techniques called Integral Ratio. They are designed to threshold gray-scale handwriting images and separate the handwriting from the background. The following tight requirements must be met: 1) all the details of the handwriting are to be retained, 2) the writing paper used may contain strong colored and/or patterned background which must be removed, and 3) the handwriting may be written using a wide variety of pens such as a fountain pen, ballpoint pen, or pencil. A specific application area which requires these tight requirements is forensic document examination, where a handwritten document is often considered as legal evidence and the handwriting must not be tampered with or modified in any way. The proposed class of techniques is based on a two stage thresholding approach requiring each pixel of a handwritten image to be placed into one of three classes: foreground, background, and a fuzzy area between them where it is hard to determine whether a pixel belongs to the foreground or the background. Two techniques, Native Integral Ratio (NIR) and Quadratic Integral Ratio (QIR), were created based on this class and tested against two well-known thresholding techniques: Otsu's technique and the Entropy thresholding technique. We found that QIR has superior performance compared to all the other techniques tested.</p>
Document image thresholding, background removal, preprocessing.
Yan Solihin, "Integral Ratio: A New Class of Global Thresholding Techniques for Handwriting Images", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.21, no. 8, pp. 761-768, August 1999, doi:10.1109/34.784289