Name
Abstract | ||
|---|---|---|
This paper presents an evolutionary approach able to process a digital image and detect tracks left by preceding vehicles on ice and snow in Antarctica. Biologically inspired by a colony of ants able to interact and cooperate to determine the shortest path to the food, this approach is based on autonomous agents moving along the image pixels and iteratively improving an initial coarse solution. The unfriendly Antarctic environment makes this image analysis problem extremely challenging, since light reflections, abruptly varying brightness conditions, and different terrain slopes must be considered as well. The ant-based approach is compared to a more traditional Hough-based solution and the results are discussed. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/TIE.2002.807688 | IEEE Transactions on Industrial Electronics |
Keywords | Field | DocType |
Hough transforms,automated highways,automatic guided vehicles,computer vision,evolutionary computation,ice,image processing,navigation,snow,Antarctic environment,Antarctica,Hough-based solution,ant-based approach,automatic vehicle guidance,autonomous agents,brightness conditions,digital image processing,evolutionary algorithms,evolutionary approach,ice,image analysis,image pixels,intelligent transportation systems,intelligent vehicles,light reflections,machine vision,preceding vehicle tracks detection,snow,terrain slopes,vehicle navigation,visual sensing | Computer vision,Evolutionary algorithm,Shortest path problem,Machine vision,Evolutionary computation,Image processing,Digital image,Pixel,Artificial intelligence,Engineering,Digital image processing | Journal |
Volume | Issue | ISSN |
50 | 1 | 0278-0046 |
Citations | PageRank | References |
15 | 1.26 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto Broggi | 1 | 1527 | 178.28 |
| Massimo Cellario | 2 | 15 | 1.26 |
| Paolo Lombardi | 3 | 15 | 1.26 |
| Marco Porta | 4 | 59 | 6.33 |