Name
Title | ||
|---|---|---|
Vision system for defect imaging, detection, and characterization on a specular surface of a 3D object |
Abstract | ||
|---|---|---|
A vision system capable of imaging, detecting, and characterizing defects onto highly reflective, non-plane surfaces, is presented in this paper. Defects are typically dust, and hair located under the metallic layer of packaging products used in cosmetic industries. The vision system comprises an innovative lighting solution to reveal defects onto highly reflective non-plane surfaces. Several image acquisitions are performed to build a synthetic image, where defects clearly appear white on a mid-gray background. Our lighting system allows imaging defects on various-shaped objects. The vision system measures the defect size to make a decision on the product rejection. The authors assess system performance by conducting series of tests. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1016/S0262-8856(02)00046-X | Image and Vision Computing |
Keywords | Field | DocType |
Defect imaging,Reflective surface,Three-dimensional object,Lighting system,Vision computing | Computer vision,Computer graphics (images),Machine vision,Specular reflection,Lighting system,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
20 | 8 | 0262-8856 |
Citations | PageRank | References |
8 | 1.00 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Denis Aluze | 1 | 8 | 1.00 |
| Fred Merienne | 2 | 9 | 1.70 |
| Christophe Dumont | 3 | 14 | 2.18 |
| Patrick Gorria | 4 | 30 | 10.56 |