Fast Recognition of Asian Characters Based on Database Methodologies

Abstract

Character recognition has been an active research area in the field of pattern recognition. The existing character recognition algorithms are focused mainly on increasing the recognition rate. However, as in the recent Google Library Project, the requirement for speeding up recognition of enormous amount of documents is growing. Moreover, the existing algorithms do not pay enough attention to Asian characters. In this paper, we propose an algorithm for fast recognition of Asian characters based on the database methodologies. Since the number of Asian characters is very large and their shapes are complicated, Asian characters require much more recognition time than numeric and Roman characters. The proposed algorithm extracts the feature from each of Asian characters through the Discrete Fourier Transform (DFT) and optimizes the recognition speed by storing and retrieving the features using a multidimensional index. We improve the recognition speed of the proposed algorithm using the association rule technique, which is a widely adopted data mining technique. The proposed algorithm has the advantage that it can be applied regardless of the language, size, and font of the characters to be recognized.