Name
Abstract | ||
|---|---|---|
The matching points extracted from images play a very important role in many applications and particularly in computer vision. The use of point sets as being characteristics that describe the entire images brought into play, it greatly contributes to the reduction of the execution time, unlike the use of all the information contained in these images. The major problem of the matching process is the possibility to generate a large number of false correspondences, or outliers, in addition to a limited number of true correspondences (inliers). The objective of this paper is to propose a robust algorithm to eliminate or reduce the false correspondences, or outliers, among the putative set extracted from stereoscopic images. The principle of our method is based on the notion of belonging to the corresponding circles and the concept of similarity of stereoscopic images. The results largely reflect the efficiency and performance of our algorithm in comparison to the other used methods in this framework like RANSAC algorithm. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s11042-017-5086-y | Multimedia Tools Appl. |
Keywords | Field | DocType |
Matching, Outliers, Putative set, Stereoscopic images | Computer vision,Point set registration,Pattern recognition,Computer science,RANSAC,Stereoscopy,Outlier,Execution time,Artificial intelligence | Journal |
Volume | Issue | ISSN |
77 | 12 | 1380-7501 |
Citations | PageRank | References |
2 | 0.37 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abderazzak Taime | 1 | 3 | 1.05 |
| Jamal Riffi | 2 | 20 | 3.97 |
| Abderrahim Saaidi | 3 | 44 | 10.56 |
| Khalid Satori | 4 | 42 | 16.75 |