5. CONCLUSIONS
In this paper we have presented a program which recog-
nizes real roads. This program can integrate the spectral
and spatial information in extraction of particular tar-
get. It can simulate the visual interpretation to recognize
the roads. The ratio of the lenth to width of road is
proved to be the special information to successful dis-
crimination of the road.
Although there are broken fragments on the road line in
the result picture, the accuracy by this program is much
better than those by conventional methods.
ACKNOWLEDGEMENT
The author carries much thanks to Prof. Zhao Yuan-
hong and Prof. Chen Lan for their lots of helps and
guidences.
REFERENCES
1. Barry, N. H. , 1984. Multisensor data analysis of
urban environments. Photogrammetric Engineering
and Remote Sensing, Vol. 50, No. 10, pp. 1471—
438
1477.
. Charlotte M. G. and J. R. G. Townshend, 1983.
The use of contextual information in the classifica-
tion of remotely sensed data. Photogrammetric Engi-
neering and Remote Sensing, Vol. 49, No. 1, pp. 55
—64.
. Philip H. Swain, Howard Jay Siegel, Bradley W.
Smith, 1980. Contextual classification of multispec-
tral remote sensing data using a multiprocessor sys-
tem. IEEE Transactions on Geoscience and Remote
Sensing, Vol. GE-18, No. 2.
. Ruzena Bajcesy , Mohamad Tavakoli, 1976. Comput-
er recognition of roads from satellite pictures. IEEE
Transactions on System, Man, and Cybernetics,
Vol. SMC-6, No. 9.
. Stephen W. Wharton, 1982. A contextual classifica-
tion method for recognizing land use patterns in high
resolution remotely sensed data. Pattern Recogni-
tion, Vol. 15, No. 4, pp. 317 —324.
Tian Lianghu, Zhao Yuanhong, Zhan Fuxiang,
1990. Urban thematic information extraction and
dynamic extension detection. Proceedings of the
11th Asian Conference on Remote Sensing, Q-37-
1-Q-37-6.
. Tian Lianghu, 1991. Detection of the developments
of urban area using remotely sensed data. Remote
Sensing Application, Vol. 4, No. 1, pp. 28—35.