텍스트와 그래픽으로 구성된 혼합문서 인식에 관한 연구

A Study on the Recognition of Mixed Documents Consisting of Texts and Graphic Images

In this paper, an efficient algorithm is proposed which recognizes the mixed document consisting of the printed Korean/alphanumeric texts and graphic images. In the preprocessing step an input document is aligned if necessary by rotating it. We obtain the rotation angle using the Hough transform and align the input document horizontally. Then we separate graphic image parts from text parts by considering chain codes of connected components. We further separate each character using vertical and horizontal projections. In the recognition step Korean and alphanumeric characters are classified and each of them is recognized hierarchically using several features. In summary an efficient recognition algorithm for mixed documents is proposed and its performance is demonstrated via computer simulations.