Name
Abstract | ||
|---|---|---|
Document image segmentation is a fundamental step in the document image analysis pipeline as it affects the accuracy of subsequent processing steps. An objective and realistic evaluation of page segmentation techniques is crucial for a quantitative comparison among them. In this paper, a goal-oriented performance evaluation methodology that calculates a comprehensive evaluation measure SR (Success Rate) is presented. SR measure reflects the entire performance of a page segmentation technique in a concise quantitative manner. It is a pixel-based approach which avoids the dependence on a strictly defined ground-truth. The proposed evaluation measure SR deals only with text regions and is correlated with the percentage of the text information in which the subsequent processing (e.g. text line segmentation and recognition) can be applied successfully. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICDAR.2015.7333768 | International Conference on Document Analysis and Recognition |
Keywords | Field | DocType |
page segmentation, performance evaluation, performance metric, document image analysis | Computer vision,Scale-space segmentation,Pattern recognition,Image texture,Segmentation,Computer science,Performance metric,Segmentation-based object categorization,Image segmentation,Pixel,Artificial intelligence,Minimum spanning tree-based segmentation | Conference |
ISSN | Citations | PageRank |
1520-5363 | 3 | 0.40 |
References | Authors | |
13 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolaos Stamatopoulos | 1 | 20 | 2.79 |
| Georgios Louloudis | 2 | 81 | 9.54 |
| Basilis Gatos | 3 | 773 | 43.34 |