A Character Segmentation Method without Character Verification

Nowadays many digital watermarking schemes have been proposed to protect paper-based documents, in which character segmentation is important in both embedding and detecting processes. However, considering the time/cost consuming, the current character segmentation methods used in OCR (optical character recognition) are not suitable for this purpose. In this paper, by incorporating the statistical structural data and the periodicity, a method to segment the mixed Chinese/English characters without OCR phase is proposed. Experimental results show that the novel method can implement character segmentation and language discrimination effectively and it will improve the performance of the digital watermarking schemes designed for paper-based documents.