The Detection of Forged Handwriting Using a Fractal Number Estimate of Wrinkliness

Handwriting experts are usually required to differentiate between authentic and forged signatures. Therefore, it is important to develop an objective system to identify forged handwriting, or at least to identify those handwritings that are likely to be forged. Forgers often forge handwriting in terms of shape and size by carefully copying or tracing the authentic handwriting. We hypothesize, therefore, that good forgeries – that is, those that retain the shape and size of authentic writing – are usually written more slowly than authentic writing. We also hypothesize that good forgeries are wrinklier (less smooth) than authentic handwriting. To examine these hypotheses we collected both online and offline data from the same handwriting samples. Experimental subjects wrote handwriting samples on paper mounted on a tablet digitizer, and the x-y coordinates of these online samples were used to calculate the speed of the handwriting. We found that the writing speed of the good forgeries was significantly slower than that of the authentic writings. The paper on which the handwriting samples were written was then digitally scanned at two different resolutions to calculate wrinkliness, which is a fractal number estimate of the jaggedness of the writing. We found that the wrinkliness of the good forgeries was significantly greater than that of the authentic writings, showing that it is possible to identify candidate forgeries from scanned documents. These studies employed the IBM ThinkPad TransNote, pen-enabled notebook computer.