DocumentCode :
2733712
Title :
Road extraction framework by using cellular neural network from remote sensing images
Author :
Sarhan, Ebada ; Khalifa, Eraky ; Nabil, Ayman M.
Author_Institution :
Comput. Sci. Dept., Helwan Univ., Cairo, Egypt
fYear :
2011
fDate :
3-5 Nov. 2011
Firstpage :
1
Lastpage :
5
Abstract :
Researches on Road Extraction are incessant. Theses researches aims at the automatic identification of remote sensing images. The way to extract roads quickly, accurately and automatically has been a cutting-edge problem in remote sensing related fields, since the availability of high spatial resolution images from new generation commercial sensors. In this paper, we present a novel automatic road extraction approach which uses a Cellular neural Network. The approach makes full use of spectral and geometric properties of roads in the imagery, and proposes a Framework named “CNN- Cellular neural Network”. A primary result shows that the accuracy of this algorithm is very high, fast and can be implemented on hardware chipset.
Keywords :
cellular neural nets; geophysical image processing; image resolution; roads; sensors; automatic identification; cellular neural network; cutting-edge problem; geometric property; hardware chipset; high spatial resolution image; new generation commercial sensor; remote sensing image; road extraction framework; spectral property; Biomedical imaging; Cellular neural networks; Image segmentation; Information processing; Mathematical model; Remote sensing; Roads; CNN; remote sensing images; road extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Information Processing (ICIIP), 2011 International Conference on
Conference_Location :
Himachal Pradesh
Print_ISBN :
978-1-61284-859-4
Type :
conf
DOI :
10.1109/ICIIP.2011.6108892
Filename :
6108892
Link To Document :
بازگشت