ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK

Dal Poz, A. P.; Mendes, T. S. G.

This paper addresses the problem of road region detection in urban areas using an image classification approach. In order to minimize the spectral superposition of the road (asphalt) class with other classes, the Artificial Neural Networks (ANN) image classification method was used to classify geometrically-integrated high-resolution RGB aerial and laser-derived images. The RGB image was combined with different laser data layers and the ANN classification results showed that the radiometric and geometric laser data allows a better detection of road pixel.

Zitieren

Zitierform:

Dal Poz, A. P. / Mendes, T. S. G.: ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK. 2013. Copernicus Publications.

Zugriffsstatistik

Gesamt:
Volltextzugriffe:
Metadatenansicht:
12 Monate:
Volltextzugriffe:
Metadatenansicht:

Grafik öffnen

Rechte

Rechteinhaber: A. P. Dal Poz

Nutzung und Vervielfältigung:

Export