State Machine Induction with Positive and Negative Training for Thai Character Recognition

One problem of generating a model to recognize any string is how to generate one that is generalized enough to accept strings with similar patterns and, at the same time, is specific enough to reject the non-target strings. This research focus on generating a model in the form of a state machine to recognize strings derived from the direction information of character's images. The state machine induction process has two steps. The first step is to generate the machine from the strings of each target character (positive training), and the second step is to adjust the machine to reject any other string (negative training). This state machine induction method that automatically learns from strings can be applied with other string patterns recognition apart from characters.