ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W4, 149-156, 2015
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W4/149/2015/
doi:10.5194/isprsannals-II-3-W4-149-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
11 Mar 2015
AUTOMATED DETECTION OF OIL DEPOTS FROM HIGH RESOLUTION IMAGES: A NEW PERSPECTIVE
A. O. Ok1 and E. Başeski2 1Dept. of Geodesy and Photogrammetry, Nevsehir H.B.V. University, 50300 Nevsehir, Turkey
2HAVELSAN A.Ş., Eskisehir Yolu 7.km, 06520 Ankara, Turkey
Keywords: Oil Depots, Radial Symmetry, Automated Detection, Aerial/Satellite Imagery Abstract. This paper presents an original approach to identify oil depots from single high resolution aerial/satellite images in an automated manner. The new approach considers the symmetric nature of circular oil depots, and it computes the radial symmetry in a unique way. An automated thresholding method to focus on circular regions and a new measure to verify circles are proposed. Experiments are performed on six GeoEye-1 test images. Besides, we perform tests on 16 Google Earth images of an industrial test site acquired in a time series manner (between the years 1995 and 2012). The results reveal that our approach is capable of detecting circle objects in very different/difficult images. We computed an overall performance of 95.8% for the GeoEye-1 dataset. The time series investigation reveals that our approach is robust enough to locate oil depots in industrial environments under varying illumination and environmental conditions. The overall performance is computed as 89.4% for the Google Earth dataset, and this result secures the success of our approach compared to a state-of-the-art approach.
Conference paper (PDF, 1708 KB)


Citation: Ok, A. O. and Başeski, E.: AUTOMATED DETECTION OF OIL DEPOTS FROM HIGH RESOLUTION IMAGES: A NEW PERSPECTIVE, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W4, 149-156, doi:10.5194/isprsannals-II-3-W4-149-2015, 2015.

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