Genetic Algorithms for Perceptual Codes Extraction
Figure 18. (a) Generation of the Arabic word “” with the
EPCs; (b) Generation of the Arabic word “” with the
In this paper, we present a new method of features ex-
traction of online handwriting. This method has attem-
pted to overcome the inherent ambiguities of handwriting
with the help of genetic algorithms. It was the difficult
part of the whole handwriting recognition system as the
features extraction had to be robust to cope up with the
handwriting variety and changes due to mood, health and
different writing styles.
To extract the GPCs of an online script we use the
Beta-elliptic model to modelise and to extract parameters
of handwriting. With the help of these parameters we de-
veloped an EPC extractor. For each elliptic arc and with
its deviation angle we define four types of EPCs. The
human visual sense is selectively activated in response to
global form. For this reason we developed a GPC ex-
tractor composed of ten GPCs. A GPC is a combination
of a set of EPCs according to well defined criteria. For
each GPC we used a genetic algorithm to optimize the
choice of a good combination (number and type of EPCs
composing the GPC) of EPCs. Finally a lot of proposi-
tion was giving by the GPC extractor to compose the
script. To choice the best and significant proposition a
stage of refinement was developed.
These GPCs can be used to develop a handwriting
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