Name
Title | ||
|---|---|---|
Handwritten character recognition using Empirical Mode Decomposition applied writing movements. |
Abstract | ||
|---|---|---|
In this paper, handwritten character recognition by using characters' writing movements is investigated. To obtain the information about writing movements a 3-axis accelerometer is used. Just like most of other sensors, 3-axis accelerometers give the actual movement signal as well as noise. Before the recognition step, all of the signals need to be preprocessed and the noisy parts need to be removed. So, Empirical Mode Decomposition (EMD) and normalization preprocessing steps are applied to the signals. Finally, the signals in the dataset are compared with Dynamic Time Warping for classification and accurate classification rate of 91.92% is obtained. |
Year | Venue | Keywords |
|---|---|---|
2017 | Signal Processing and Communications Applications Conference | 3-axis accelerometer,emprical mode decomposition,dynamic time warping,handwritten character recognition |
Field | DocType | ISSN |
Normalization (statistics),Dynamic time warping,Computer science,Gesture recognition,Artificial intelligence,Computer vision,Pattern recognition,Character recognition,Accelerometer,Speech recognition,Preprocessor,Classification rate,Hilbert–Huang transform | Conference | 2165-0608 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Esra Tuncer | 1 | 0 | 0.34 |
| Bilal Orkan Olcay | 2 | 0 | 1.35 |
| Mehmet Zubeyir Unlu | 3 | 0 | 1.35 |