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Automatic Finding of Main Roads in Aerial Images by Using Geometric-Stochastic Models and Estimation
July 1996 (vol. 18 no. 7)
pp. 707-721
Abstract—This paper presents an automated approach to finding main roads in aerial images. The approach is to build geometric-probabilistic models for road image generation. We use Gibbs Distributions. Then, given an image, roads are found by map (maximum a posteriori probability) estimation. The map estimation is handled by partitioning an image into windows, realizing the estimation in each window through the use of dynamic programming, and then, starting with the windows containing high confidence estimates, using dynamic programming again to obtain optimal global estimates of the roads present. The approach is model-based from the outset and is completely different than those appearing in the published literature. It produces two boundaries for each road, or four boundaries when a mid-road barrier is present.
[1] 707 R. Nevatia and K.R. Babu, "Linear Feature Extraction and Description," IEEE CGIP, pp. 257-269, 1980.[2] Z. Aviad and J.P.D. Carnine, "Road Finding for Road Network Extraction," CMU-CS-88-157, 1988.[3] D.M. McKeown and L. Denlinger, "Cooperative Methods for Road Tracing in Aerial Imagery," CVPR, 1988.[4] L. Quam, "Road Tracing and Anomaly Detection in Aerial Imagery," Proc. Darpa Image Understanding Workshop, pp. 51-55, 1978.[5] W. Kestner and H. Kazmierzak, "Semiautomatic Extraction of Roads from Aerial Photographs," Research Inst. for Information Processing and Pattern Recognition, 1978.[6] R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis.New York: John Wiley, 1973.[7] J. Boggess, "Identification of Roads in Satellite Imagery Using Artificial Neural Networks: A Contextual Approach," technical report, Mississippi State Univ., Aug. 1993.[8] J.M. Fischler and H. Wolk, "Detection of Roads and Linear Structures in Low-Resolution Aerial Imagery Using a Multisource Knowledge Integration Technique," CGIP, pp. 201-223, Aug. 1981.[9] D. Geman and B. Jedynak, "An Active Testing Model for Tracking Roads in Satellite Images," technical report, Univ. of Massachusetts at Amherst, Aug. 1994.[10] D. Cooper, "Maximum Likelihood Estimation of Markov Process Blob Boundaries in Noisy Images," IEEE Trans. Pattern Analysis and Machine Intelligence, Oct. 1979.[11] D.B. Cooper and F.P. Sung, "Multiple-Window Parallel Adaptive Boundary Finding in Computer Vision," IEEE Trans. Pattern Analysis and Machine Intelligence, 1983.[12] M. Barzohar and D.B. Cooper,“Automatic finding of main roads in aerial images by using geometric-stochastic models and estimation,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 459-464, 1993.[13] M. Barzohar and D.B. Cooper, "Completely Automatic Reliable Finding of Main Roads in Aerial Images by Using Bayesian Methods," Brown-LEMS-118, Mar. 1993.[14] C. Graffine and I. Herlin, "Modélisation de réseaux pour l'imagerie satellite spot," technical report, INRIA, 1989.[15] D. Geiger, A. Gupta, L.A. Costa, and J. Vlontzos, Dynamical Programming for Detecting, Tracking and Matching Deformable Contours IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 3, pp. 294-302, Mar. 1995.
Index Terms:
Geometric-probabilistic models, Gibbs distributions, maximum a posteriori probability estimation, road geometry model, Gaussian driving noise, dynamic programming, model-based segmentation.
Citation:
Meir Barzohar, David B. Cooper, "Automatic Finding of Main Roads in Aerial Images by Using Geometric-Stochastic Models and Estimation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 7, pp. 707-721, July 1996, doi:10.1109/34.506793
