Name
Abstract | ||
|---|---|---|
Object recognition often operates by making decisions based on the values of several shape properties measured from an image of the object. In this paper, we propose a new exploitation of the Radon Transform using the gradient measurement to generate a new signature (GR-signature) which provides global information of a binary shape regardless its form. We also develop a new method for measuring the rectangularity based on GR-signature. This original approach looks very promising and has several useful properties that keep fundamental geometrical transformations like scale, rotation and translation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21587-2_15 | MCPR |
Keywords | Field | DocType |
global information,object recognition,fundamental geometrical transformation,new signature,binary shape,new exploitation,gradient measurement,new method,radon transform,shape property | Computer vision,Computer science,Global information,Artificial intelligence,Radon transform,Cognitive neuroscience of visual object recognition,Binary number | Conference |
Citations | PageRank | References |
2 | 0.39 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jihen Hentati | 1 | 2 | 0.39 |
| Mohamed Naouai | 2 | 13 | 2.85 |
| Atef Hamouda | 3 | 40 | 12.57 |
| Christiane Weber | 4 | 15 | 2.56 |