Off-line recognition of Korean scripts using distance matching and neural network classifiers
Soo-Hyung Kim, Jeong-In Doh · 2002
An off-line recognition engine is proposed for handwritten Korean characters based on a distance matching and the neural network technique. The distance matching selects a set of several candidates from the large set of character classes, and the neural network performs a detailed classification on the candidates. As an approach for combining the two methodologies, a clustering method based on sample distributions has been devised. Recognition accuracy of the engine on a public database, PE92, is 84.1%. About four character patterns can be processed in a second on PC.