Fig. 4: The whole process used to extract the frequency spectrum of our signal.
From: The transferability of handwriting skills: from the Cyrillic to the Latin alphabet
(1) We first divided the BHK text into bins of 600 points. (2) For each bin, the signal was extracted. (3) We then computed the Fourier transformation of each signal. (4) We took the average of all signals and finally performed a normalization. At the top of the figure there is an example of a signal extracted from the data: the red dots are the point coordinates recorded by the device during handwriting. The vectors in blue are “local'” vectors linking two consecutive points. The vector in green is the “global” vector (average of the nine blue vectors) representing the global direction of the handwriting. The cross product of these two vectors gives us an indication of the smoothness/shakiness of the handwriting. The image on the right comes from a writer with smoother/less shaky handwriting than the one on the left. The cross product operation will detect this difference. The figure comes from21.
