Oil Tank Detection in Satellite Images via a Contrario Clustering

Monitoring oil stocks provides valuable insights on the balance between production and demand of petroleum products. The identification of oil depots is important for estimating storage capacities and measuring oil stocks. To achieve this purpose, we present an oil tank detector. As oil tanks are generally circular, we use as a first step a circle detection algorithm. However, this approach tends to generate a considerable amount of false detections, as circular shapes are not necessarily tanks. To reduce these false detections, we take advantage of the fact that oil tanks are generally densely grouped together, and filter out isolated detections using a clustering algorithm. The clustering method uses the a contrario framework which gives a way to control the number of false detections per image. The method is illustrated on Sentinel-2 images.