Name
Title | ||
|---|---|---|
Text line segmentation using a fully convolutional network in handwritten document images. |
Abstract | ||
|---|---|---|
Line detection in handwritten documents is an important problem for processing of scanned documents. While existing approaches mainly use hand-designed features or heuristic rules to estimate the location of text lines, the authors present a novel approach that trains a fully convolutional network (FCN) to predict text line structure in document images. A rough estimation of text line, or a line m... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-ipr.2017.0083 | IET Image Processing |
Keywords | Field | DocType |
document image processing,edge detection,graph theory,handwritten character recognition,image segmentation,neural nets,text detection | Adjacency list,Computer vision,Graph,Heuristic,Pattern recognition,Segmentation,Image segmentation,Robustness (computer science),Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
12 | 3 | 1751-9659 |
Citations | PageRank | References |
0 | 0.34 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Quang Nhat Vo | 1 | 1 | 1.35 |
| Soo-Hyung Kim | 2 | 191 | 49.03 |
| Hyungjeong Yang | 3 | 455 | 47.05 |
| Gueesang Lee | 4 | 208 | 52.71 |