Name
Abstract | ||
|---|---|---|
In this paper, we present a system to recognize text in traffic signs, along with its context based recognition result corrections that we developed. This system detects text in traffic signs region using contour detection and using KNN Classifier to recognize letters in it. The result of the recognitions that may contain errors will be corrected using Forward Reverse Dictionary that has Contextual Database. This testing is done for recognition system without correction and recognition system with correction on a sample sign. This implementation increases the accuracy rate of word recognition by 10% at 10% noise on a 100% area which is quite good. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICSEngT.2016.7849635 | 2016 6th International Conference on System Engineering and Technology (ICSET) |
Keywords | Field | DocType |
Traffic Signs Text,KNN,Forward Reversed Dictionary,Contextual Database,Word Relations,Context | Pattern recognition,Intelligent character recognition,Context based,Computer science,Word recognition,Error detection and correction,Speech recognition,Artificial intelligence,Intelligent transportation system,Classifier (linguistics),Reverse dictionary,Text recognition | Conference |
ISSN | ISBN | Citations |
2470-640X | 978-1-5090-5090-1 | 0 |
PageRank | References | Authors |
0.34 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Didit Andri Jatmiko | 1 | 0 | 0.34 |
| Ary Setijadi Prihatmanto | 2 | 0 | 3.72 |