Name
Abstract | ||
|---|---|---|
This paper presents a parameter-free document binarization method based on text characteristics. For a given stroke width, the text and background regions in binarized object regions are estimated with morphological operators. Then according to the numbers of the text and background pixels an optimal threshold is determined. To make the proposed method parameter-free, an automatic estimation of stroke width is also proposed based on the ratio of thick stroke pixels to binarized object pixels. Document images with various degenerations, such as stain and bleed-through, were used to test the proposed method. Comparison results demonstrate that our method can achieve a better performance than Otsu’s, Kwon’s, Chen’s, Transition, and Moghaddam’s binarization methods. |
Year | Venue | Field |
|---|---|---|
2015 | ICIG | Computer vision,Pattern recognition,Computer science,Artificial intelligence,Operator (computer programming),Pixel |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
14 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiang Chen | 1 | 604 | 57.44 |
| Qing Wang | 2 | 46 | 15.29 |
| Sheng-tao Lu | 3 | 0 | 0.34 |
| Yu-ping Wang | 4 | 0 | 0.34 |