The Generalized Multi Scaled Radon Transform and Application on Objects Classification

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.