Name
Abstract | ||
|---|---|---|
The document digitization process becomes a crucial economical issue in our society. Then, it becomes necessary to be able to organize this huge amount of documents. The work proposed in this paper tends to propose a new method to automatically classify documents using a saliency-based segmentation process on one hand, and a terminology extraction and annotation on the other hand. The saliency-based segmentation is used to extract salient regions and by the way logo, while the terminology approach is used to annotate them and to automatically classify the document. The approach does not require human expertise, and use Google Images as a knowledge database. The results obtained on a real database of 1766 documents show the relevance of the approach. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-662-44854-0_8 | GRAPHICS RECOGNITION: CURRENT TRENDS AND CHALLENGES |
Field | DocType | Volume |
Document classification,Computer vision,Digitization,Information retrieval,Terminology,Salience (neuroscience),Computer science,Segmentation,Logo,Artificial intelligence,Knowledge base,Terminology extraction | Conference | 8746 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benjamin Duthil | 1 | 8 | 3.69 |
| Mickaël Coustaty | 2 | 48 | 26.25 |
| Vincent Courboulay | 3 | 66 | 12.07 |
| Jean-Marc Ogier | 4 | 631 | 85.80 |