Name
Title | ||
|---|---|---|
A morphological neural network approach for vehicle detection from high resolution satellite imagery |
Abstract | ||
|---|---|---|
This paper introduces a morphological neural network approach to extract vehicle targets from high resolution panchromatic satellite imagery. In the approach, the morphological shared-weight neural network (MSNN) is used to classify image pixels on roads into vehicle targets and non-vehicle targets, and a morphological preprocessing algorithm is developed to identify candidate vehicle pixels. Experiments on 0.6 meter resolution QuickBird panchromatic data are reported in this paper. The experimental results show that the MSNN has a good detection performance. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11893257_11 | ICONIP |
Keywords | Field | DocType |
vehicle detection,morphological preprocessing algorithm,vehicle target,candidate vehicle pixel,morphological neural network approach,image pixel,meter resolution quickbird panchromatic,high resolution panchromatic satellite,high resolution satellite imagery,good detection performance,morphological shared-weight neural network,neural network,high resolution | Computer vision,Satellite imagery,Pattern recognition,Computer science,Panchromatic film,Vehicle detection,Metre (music),Artificial intelligence,Pixel,Artificial neural network,Preprocessing algorithm | Conference |
Volume | ISSN | ISBN |
4233 | 0302-9743 | 3-540-46481-6 |
Citations | PageRank | References |
4 | 0.55 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Zheng | 1 | 14 | 3.29 |
| Li Pan | 2 | 20 | 3.13 |
| Li Li | 3 | 8 | 1.88 |