Name
Abstract | ||
|---|---|---|
Scene text detection is attracting more and more attention and has become an important topic in machine vision research. With the development of mobile IoT (Internet of things) and deep learning technology, text detection research has made significant progress. This survey aims to summarize and analyze the main challenges and significant progress in scene text detection research. In this paper, we first introduce the history and progress of scene text detection and classify the traditional methods and deep learning-based methods in detail, pointing out the corresponding key issues and techniques. Then, we introduce commonly used benchmark datasets and evaluation protocols and identify state-of-the-art algorithms by comparison. Finally, we summarize and predict potential future research directions. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/sym12121956 | SYMMETRY-BASEL |
Keywords | DocType | Volume |
scene text detection, natural images, deep learning, detection framework | Journal | 12 |
Issue | Citations | PageRank |
12 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongping Cao | 1 | 0 | 0.68 |
| Yong Zhong | 2 | 0 | 1.35 |
| Lishun Wang | 3 | 0 | 0.34 |
| Yilong He | 4 | 0 | 0.34 |
| Jiachen Dang | 5 | 0 | 0.68 |