A Static Candidates Generation Technique and its Application in Two-stage LDA Chinese Character Recognition

As an effective tool for feature selection, liner discriminate analysis (LDA) has been widely used in the field of Chinese Character Recognition. In this paper, we propose a novel static candidates generation technique, which significantly reduces the storage and the computational complexity of the traditional LDA. Using the proposed technique, a two-stage LDA recognition scheme for Chinese character recognition is presented. Compared with minimum distance classifier and LDA plus minimum distance classifier, the error ratio of proposed scheme significantly decline 60% and 35% respectively, which shows the validity of the proposed approach.