Oil tank is one kind of foundational industrial facility for storage of oil and petrochemical products. Automatic recognition of the oil depot in the remote sensing image is of important practical significance in many fields. Nowadays, the Unmanned Aerial Vehicle (UAV) provides an available alternative solution to the satellite for monitoring the oil depot, owing to its advantages of flexibility, rapid response and minimal cost. In this paper, a novel oil tank extraction method based on detection of the elliptic rooftop is proposed. To start with, straight line segments of object boundary are extracted in the UAV imagery. Secondly, these lines are linked to form arc segments based on proper geometric criteria, and then elliptical rooftops are extracted based on these arcs to generate hypotheses of potential oil tanks. Finally, within Region of Interest (ROI) of rooftops, hypotheses disambiguation and verification of targets are accomplished primarily by extraction of facade contours of oil tanks. Experimental results demonstrate the good performance of our method on a variety of complex scenes.
This paper proposes a new image registration method based on grade-by-grade matching in interferometric inverse
synthetic aperture radar (InISAR) imaging system using two antennas. The causation and quantitative analysis of the
offset between two ISAR images for different antennas along each baseline is analyzed. Strong scatterer centers (SSCs)
are extracted from the ISAR images of each antenna by OTSU method firstly. A standard matching is calculated by the
image centroid. Then a mapping of region of interest (ROI) and correlation is carried out to get the precise registration.
Simulation results demonstrate that the offset between two ISAR images can be compensated effectively when the
proposed method is used, achieving a high quality 3D InISAR image consequently.
Airport runway recognition is of great significance in fields like remote sensing, navigation and traffic monitoring. An airport runway recognition method using the “hypothesize-and-verify” paradigm is proposed. Firstly, local line segments of runway contour are extracted in complex infrared image. Secondly, basing on a new Line Segment Hough Transform, local line segments vote fuzzily in the parameter space to obtain global line segment clustering, and then parallel straight lines are extracted on the basis of parameter space to form hypotheses of potential airport runways. Finally, using contextual information of airport constructions, hypotheses disambiguation and verification of runway is accomplished primarily by extraction of runway markings and segmentation of transportation network, i.e. taxiways and apron. Experimental results demonstrate the good performance of our method on a variety of complex scenes.
An approach to infrared ship detection based on sea-sky-line(SSL) detection, ROI extraction and feature recognition is proposed in this paper. Firstly, considering that far ships are expected to be adjacent to the SSL, SSL is detected to find potential target areas. Radon transform is performed on gradient image to choose candidate SSLs, and detection result is given by fuzzy synthetic evaluation values. Secondly, in view of recognizable condition that there should be enough differences between target and background in infrared image, two gradient masks have been created and improved as practical guidelines in eliminating false alarm. Thirdly, extract ROI near the SSL by using multi-grade segmentation and fusion method after image sharpening, and unsuitable candidates are screened out according to the gradient masks and ROI shape. Finally, we segment the rest of ROIs by two-stage modified OTSU, and calculate target confidence as a standard measuring the facticity of target. Compared with other ship detection methods, proposed method is suitable for bipolar targets, which offers a good practicability and accuracy, and achieves a satisfying detection speed. Detection experiments with 200 thousand frames show that the proposed method is widely applicable, powerful in resistance to interferences and noises with a detection rate of above 95%, which satisfies the engineering needs commendably.