Stroke width transform for linear structure detection: Application to river and road extraction from high-resolution satellite images

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Abstract

The evaluation of lines of communication status in normal times or during crises is a very important task for many applications, such as disaster management and road network maintenance. However, due to their large geographic extent, the inspection of the these structures surfaces using traditional techniques such as laser scanning poses a very challenging problem. In this context, satellite images are pertinent because of their ability to cover a large part of the surface of communication lines, while offering a high level of detail, which makes it possible to discriminate objects forming these linear structures. In this paper, a novel approach for extracting linear structures from high-resolution optical and radar satellite images is presented. The proposed technique is based on the Stroke Width Transform (SWT), which allows parallel edges extraction from the input image. This transform has been successfully applied in the literature to extract characters from complex scenes based on their parallel edges. An adaptation of this transform to solve the problem of rivers extraction from Synthetic Aperture Radar (SAR) images and roads identification from optical images is described in this paper, and the results obtained show the efficiency of our approach.

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Sghaier, M. O., Hammami, I., Foucher, S., & Lepage, R. (2017). Stroke width transform for linear structure detection: Application to river and road extraction from high-resolution satellite images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10317 LNCS, pp. 605–613). Springer Verlag. https://doi.org/10.1007/978-3-319-59876-5_67

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