Recognizing chinese characters through interactive activation and competition

Abstract

Most conventional approaches to Chinese character recognition attempt to recognize unknown Chinese characters per se. Hence the discriminative power of features employed play a crucial role in determining the ultimate recognition rate. However, high level linguistic knowledge such as the strong word context effects present in the Chinese language and the different frequencies of words in the daily use of the language, are not utilized in machine recognition of Chinese characters. In this paper, a word-oriented recognizer using the Interactive Activation and Competition model (IAC model) is proposed. Such a recognizer is tolerant to noise, size and font variations and it also possesses self-learning capability. © 1990.