Adaptive recognition of online, cursive handwriting.
Lambert Schomaker, Eric L Helsper, Hans-Leo H. M. Teulings, Gerben Abbink · 1993
In earlier studies, a stroke-oriented recognizer (VHS) of on-line cursive handwriting is reported [Thomassen et al., 1988; Schomaker & Teulings, 1990; Teulings et al., 1990; Schomaker & Teulings, 1992; Schomaker, 1993]. This system uses a movement-theoretical segmentation into strokes as the starting point of the recognition process. The pen-tip trajectory of a written word is low-pass filtered, and geometrically normalized with respect to size and slant. The absolute velocity of the pen-tip displacement is calculated, and the signal is segmented in strokes, each stroke being the trajectory between two robust minima in the absolute velocity [Teulings et al., 1987]. Strokes are characterized by feature vectors that are clustered using a Kohonen Self-Organizing Map as a feature quantizer. In the current system, as opposed to earlier versions, a number of typical problems in connected-cursive and mixed-cursive script recognition are dealt with, such as t-bar crossing,...