Recognition of handprinted Thai characters using the cavity features of character based on neural network

This paper describes a method of cavity features and use of neural network for recognizing handprinted Thai characters, The recognition process is implemented using mathematical morphology to detect the cavity features of patterns, and learning to classify by neural network. The recognition divided into three stages. First, the handprinted Thai characters are segmented from the sentence into three different level groups. Then, the cavity features of each handprinted Thai character are detected, and numbers counted by the Euler number method. Finally, the article uses the majority area of the cavity features for computing the feature codes of the characters in each class. These codes are trained by neural network for learning the classification characters