Abstract
In this paper, we propose an approach based on Kolmogorov Complexity (KC) measure for determining script classes in mixed Chinese (complex characters)/English document images. This approach, which mainly consists of two steps: document image preprocessing and KC measure, can successfully separate Chinese text lines from English ones. Our approach is robust and reliable in handling document images of different appearances and densities, and various fonts, sizes and styles of characters used in documents. Experimental results on a set of 40 text line images (20 English text lines and 20 Complex Chinese text lines) from various document images show that 100% correct classification rate can be achieved.
Original language | English |
---|---|
Pages (from-to) | 686-692 |
Number of pages | 7 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 4875 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Jan 2002 |
Event | Second International Conference on Image and Graphics - Hefei, China Duration: 16 Aug 2002 → 18 Aug 2002 |
Keywords
- Document image processing
- Kolmogorov complexity
- Scrip determination
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Condensed Matter Physics