Framework design and implementation for oil tank detection in optical satellite imagery

Zhu, Chenxian; Liu, Bin; Zhou, Yuhao; Yu, Qiuze; Liu, Xingzhao; Yu, Wenxian

doi:10.1109/igarss.2012.6352236

Cited by 21 publications

(9 citation statements)

References 5 publications

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“…In recent years, many oil tank detection methods have been proposed, which include the template matching method [1,2], geometric shape method [3][4][5][6][7], saliency detection method [8,9], and machine learning method [10][11][12]. The template matching method requires lots of calculations.…”

Section: Introductionmentioning

confidence: 99%

“…Han [5] uses a depth-first map search strategy, grouping the detected circles according to the special distribution of the oil tank and then eliminating false alarms. Ref [6] applies semantic analysis to retrieve the oil tank area and combines this with the Hough transform to detect oil tanks in the optical satellite images. However, this method is only used for specific images including big targets and is not universal.…”

Section: Introductionmentioning

confidence: 99%

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Unsupervised Saliency Model with Color Markov Chain for Oil Tank Detection

et al. 2019

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Traditional oil tank detection methods often use geometric shape information. However, it is difficult to guarantee accurate detection under a variety of disturbance factors, especially various colors, scale differences, and the shadows caused by view angle and illumination. Therefore, we propose an unsupervised saliency model with Color Markov Chain (US-CMC) to deal with oil tank detection. To avoid the influence of shadows, we make use of the CIE Lab space to construct a Color Markov Chain and generate a bottom-up latent saliency map. Moreover, we build a circular feature map based on a radial symmetric circle, which makes true targets to be strengthened for a subjective detection task. Besides, we combine the latent saliency map with the circular feature map, which can effectively suppress other salient regions except for oil tanks. Extensive experimental results demonstrate that it outperforms 15 saliency models for remote sensing images (RSIs). Compared with conventional oil tank detection methods, US-CMC has achieved better results and is also more robust for view angle, shadow, and shape similarity problems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Unsupervised Saliency Model with Color Markov Chain for Oil Tank Detection

et al. 2019

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“…Soon after, Han and Fu proposed a saliency model for the detection of circular storage tanks with well-defined boundaries [14]. Zhu et al developed a coarse-to-fine strategy in which the coarse level aimed at finding the image patches with oil tanks and the fine level detected the circular regions [15]. Kushwaha et al proposed a supervised strategy to detect bright oil tanks from satellite images, based on statistical and textural information [16].…”

Section: Introductionmentioning

confidence: 99%

Circular Oil Tank Detection From Panchromatic Satellite Images: A New Automated Approach

Baseski

2015

IEEE Geosci. Remote Sensing Lett.

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This letter introduces a new approach for the automated detection of circular oil tanks from single panchromatic satellite images. The new approach considers the symmetric nature of the circular oil depots, and it computes the radial symmetry in a unique way. We propose an automated thresholding method to focus on circular regions and a new measure, circle support ratio, to verify detected circles. Experiments are performed on GeoEye-1 test scenes, and the results reveal that the new approach is capable of detecting oil tanks with high success. The performance of our approach is also compared with leading techniques from the literature and has provided comparable or superior results.Index Terms-Circle detection, oil tanks, panchromatic satellite imagery, radial symmetry.

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“…So how to detect them automatically is important for many domains such as disaster monitoring, oil leakage, land environment and mapping. Some automatic oil tank detection algorithms are available in the literature 14 . In these algorithms, template matching 7 and Hough transform 8 are often used to detect oil tanks automatically.…”

Section: Introductionmentioning

confidence: 99%

Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images

Kushwaha¹,

Chaudhuri²,

Singh³

2013

DSJ

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Automatic target detection like oil tank from satellite based remote sensing imagery is one of the important domains in many civilian and military applications. This could be used for disaster monitoring, oil leakage, etc. We present an automatic approach for detection of circular shaped bright oil tanks with high accuracy. The image is first enhanced to emphasize the bright objects using a morphological approach. Then, the enhanced image is segmented using split-and-merge segmentation technique. Here, we introduce a knowledge base strategy based on the region removal technique and spatial relationship operation for detection of possible oil tanks from the segmented image using minimal spanning tree. Lastly, we introduce a supervised classifier, for identification of oil tanks, based on the knowledge database of large amount data of oil tanks. The uniqueness of the proposed technique is that it is useful for detection bright oil tanks from high as well as low resolution images, but the technique is always better for high-resolution imagery. We have systematically evaluated the algorithm on different satellite images like IRS -1C, IKONOS, QuickBird, and CARTOSAT -2A. The proposed technique is detected bright structures but unable to detect the dark structure. If the oil tank structures are bright relative to the background illumination in the image then the detection accuracy by the proposed technique for the high resolution image is more than 95 per cent.

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Framework design and implementation for oil tank detection in optical satellite imagery

Cited by 21 publications

References 5 publications

Unsupervised Saliency Model with Color Markov Chain for Oil Tank Detection

Unsupervised Saliency Model with Color Markov Chain for Oil Tank Detection

Circular Oil Tank Detection From Panchromatic Satellite Images: A New Automated Approach

Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images

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