Detection of Fragmented Rectangular Enclosures in Very-High-Resolution Remote Sensing Images
Detection of Fragmented Rectangular Enclosures in Very-High-Resolution Remote Sensing Images
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2016
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IEEE Transactions on Geoscience and Remote Sensing ; 54 (2016), 8. - pp. 4580-4593. - ISSN 0196-2892. - eISSN 1558-0644
Abstract
We develop an approach for the detection of ruins of livestock enclosures (LEs) in alpine areas captured by high-resolution remotely sensed images. These structures are usually of approximately rectangular shape and appear in images as faint fragmented contours in complex background. We address this problem by introducing a rectangularity feature that quantifies the degree of alignment of an optimal subset of extracted linear segments with a contour of rectangular shape. The rectangularity feature has high values not only for perfectly regular enclosures but also for ruined ones with distorted angles, fragmented walls, or even a completely missing wall. Furthermore, it has a zero value for spurious structures with less than three sides of a perceivable rectangle. We show how the detection performance can be improved by learning a linear combination of the rectangularity and size features from just a few available representative examples and a large number of negatives. Our approach allowed detection of enclosures in the Silvretta Alps that were previously unknown. A comparative performance analysis is provided. Among other features, our comparison includes the state-of-the-art features that were generated by pretrained deep convolutional neural networks (CNNs). The deep CNN features, although learned from a very different type of images, provided the basic ability to capture the visual concept of the LEs. However, our handcrafted rectangularity-size features showed considerably higher performance.
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ZINGMAN, Igor, Dietmar SAUPE, Otavio A. B. PENATTI, Karsten LAMBERS, 2016. Detection of Fragmented Rectangular Enclosures in Very-High-Resolution Remote Sensing Images. In: IEEE Transactions on Geoscience and Remote Sensing. 54(8), pp. 4580-4593. ISSN 0196-2892. eISSN 1558-0644. Available under: doi: 10.1109/TGRS.2016.2545919BibTex
@article{Zingman2016Detec-32382, year={2016}, doi={10.1109/TGRS.2016.2545919}, title={Detection of Fragmented Rectangular Enclosures in Very-High-Resolution Remote Sensing Images}, number={8}, volume={54}, issn={0196-2892}, journal={IEEE Transactions on Geoscience and Remote Sensing}, pages={4580--4593}, author={Zingman, Igor and Saupe, Dietmar and Penatti, Otavio A. B. and Lambers, Karsten} }
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