Name
Title | ||
|---|---|---|
The Generalized Multi Scaled Radon Transform And Application On Objects Classification |
Abstract | ||
|---|---|---|
This paper presents a Generalized Multi Scaled Radon Transform (GMSRT) which can detect parametric curves and objects of any position, orientation and scale. This new transform extends the Generalized Multi Directional Radon Transform (GMDRT) in order to outperform its recognition rates. Despite the great success of GMDRT for the geometric shape detection, it still limited in dealing with the scale variation issue. Our proposed approach combines the GMDRT and Wavelet Transform (WT) to recognize shapes with different scales. We have observed a clear improvement in terms of classification accuracy compared to the GMDRT. Experiments of the proposed approach is done on the MPEG7 dataset. Comparison with some previous approaches demonstrates the efficiency of the proposed approach in detecting complex objects, even under geometric transformations. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/AICCSA.2017.203 | 2017 IEEE/ACS 14TH INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA) |
Keywords | Field | DocType |
multi scaled Generalized Radon transform, object classification, Wavelet transform | Parametric equation,Pattern recognition,Computer science,Transformation geometry,Radon,Feature extraction,Real-time computing,Image segmentation,Artificial intelligence,Geometric shape,Radon transform,Wavelet transform | Conference |
ISSN | Citations | PageRank |
2161-5322 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dhekra El Hamdi | 1 | 0 | 0.34 |
| Ines Elouedi | 2 | 3 | 3.13 |
| Maï K. Nguyen | 3 | 62 | 12.97 |
| Atef Hamouda | 4 | 40 | 12.57 |