Experimental results of using rough sets for printed Thai characters recognition

Abstract

This paper proposes the experimental results of using a Rough sets for the recognition of printed Thai characters. In our experiment, we segment each character into 32 pieces sized 4×4 pixels, and then find the distribution of pixels that match a value of "1" (black dot) in each section Following this, we use the resulting 32 values as the attributes for each given object. Afterwards, we create 3 sets of decision making rules from 3 different training sets and use those 3 set of rules to classify each member of the unknown set. This set is composed of 42 Thai characters, excluding the two that are very rarely used, with 7 fonts and 7 sizes, for a total of 2058. The results are 46.20%, 63.15%, 73.12% for the first set of rules, the second set of rules and the third set of rules respectively. And the results when apply the set of rule to the unknown which related to each set of rules's training sets are 100% for all three set of rules.