Name
Abstract | ||
|---|---|---|
In the micro-vision system, precise calibration of the pixel equivalent is a prerequisite for accurate visual inspection. Traditional calibration process not only needs to take standard parts as the base, but also has strict requirements on their shape, manufacturing precision, placement and so on. Because of such shortcomings of traditional method, this paper gives an improved SIFT calibration algorithm for the pixel equivalent. Firstly, get the image's characteristic points before and after its' moving. using SIFT algorithm. Then filter the mismatched points through the second filtering algorithm so that the matching accuracy can be greatly improved. Compare moving distances of the characteristic point pixels to the reference distance of optical grating. Then accurate pixel equivalents can be obtained. Experiments show that the calibration algorithm is more accurate than traditional methods. So this algorithm can completely replace the standard-parts method in micro-vision system. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-27275-2_30 | COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE V, PT III |
Keywords | Field | DocType |
Vision measurement, Calibration, Feature Matching | Calibration algorithm,Scale-invariant feature transform,Computer vision,Visual inspection,Pattern recognition,Filter (signal processing),Feature matching,Pixel,Diffraction grating,Artificial intelligence,Calibration,Mathematics | Conference |
Volume | Issue | ISSN |
370 | PART 3 | 1868-4238 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hu Tao | 1 | 70 | 9.94 |
| Hui-lan Wu | 2 | 0 | 0.34 |
| Guodong Liu | 3 | 17 | 7.50 |