Name
Abstract | ||
|---|---|---|
This article discusses the quality assessment of binary images. The customary, ground truth based methodology, used in the literature is shown to be problematic due to its subjective nature. Several previously suggested alternatives are surveyed and are also found to be inadequate in certain scenarios. A new approach, quantifying the adherence of a binarization to its document image is proposed and tested using six different measures of accuracy. The measures are evaluated experimentally based on datasets from DIBCO and H-DIBCO competitions, with respect to different kinds of binarization degradations. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICFHR.2016.0097 | 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) |
Keywords | Field | DocType |
ground truth,binarization,evaluation,quality measure | Computer science,Binary image,Ground truth,Artificial intelligence,Machine learning,Grayscale | Conference |
ISSN | ISBN | Citations |
2167-6445 | 978-1-5090-0982-4 | 0 |
PageRank | References | Authors |
0.34 | 23 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arie Shaus | 1 | 12 | 2.64 |
| Barak Sober | 2 | 3 | 2.11 |
| Eli Turkel | 3 | 84 | 14.00 |
| Eli Piasetzky | 4 | 12 | 1.97 |