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A Method for Selecting Constrained Hand-Printed Character Shapes for Machine Recognition
January 1982 (vol. 4 no. 1)
pp. 74-78
Rajjan Shinghal, Department of Computer Science, Con-cordia University, Montreal, P.Q., Canada.
Ching Y. Suen, Department of Computer Science, Con-cordia University, Montreal, P.Q., Canada.
Since handwritten characters vary in shape and writing-stroke sequence, it is desirable to develop a standard set of characters that are of high quality, so that not only are they easy to write, but they are also most suitable for machine recognition. A database of more than 100 000 alphanumeric patterns was assembled. It consisted of 174 models of the alphanumeric characters written by both left-handed and right-handed subjects. Based on frequency density and distance measurements, a nietric called the dispersion factor was computed to rank the various models. The principle of the metric is discussed, and results are given indicating the high quality models of the alphanumerics.
Citation:
Rajjan Shinghal, Ching Y. Suen, "A Method for Selecting Constrained Hand-Printed Character Shapes for Machine Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 1, pp. 74-78, Jan. 1982, doi:10.1109/TPAMI.1982.4767199
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