Name
Abstract | ||
|---|---|---|
There are many challenges addressed in MRC compression, such as the segmentation of the document into foreground and background layers, represented as a binary mask. Usually, the resulting quality of a MRC compression method depends on the segmentation algorithm used to compute the binary mask. The aim of this work is to leverage state-of-the-art techniques in document segmentation allowing further content, such as text or images, to be exploited in an efficient way. Then, a novel methodology is proposed that leads to increasing document segmentation performance for MRC compression scheme. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1142/S0218126617501523 | JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS |
Keywords | Field | DocType |
Documents segmentation,MRC compression,foreground,background | Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Document segmentation,Segmentation-based object categorization,Artificial intelligence,Binary number | Journal |
Volume | Issue | ISSN |
26 | 10 | 0218-1266 |
Citations | PageRank | References |
0 | 0.34 | 30 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jassem Mtimet | 1 | 1 | 1.02 |
| Hamid Amiri | 2 | 86 | 19.36 |