Wires do not have linear structure to aid their detection when they are not lying straight. This paper proposes some features for curved wire detection from the images constructed by the data of a ground penetrating radar. We propose the application of a parabola to model a curved wire, where the detection confidence corresponds to how well the curved pattern in the image fits to a parabola. The processing involves projecting the 3-D GPR beamformed image onto the ground plane, applying the Canny edge detector to extract the edge points, and fitting the edge points to a parabola through a voting scheme as in the generalized Hough Transform. The features consist of the orientation angle, the fitted parabolic parameters and the fitting confidence. Some examples for the detection performance are illustrated.
Ellipse feature appears in the cross-section of a wire, and it can complement the line feature to improve wire detection. The previously proposed ellipse feature extraction method requires a wire to be placed parallel or perpendicular to the cross-track. It is, however, difficult to guarantee in practice. This work advances ellipse feature extraction so that we will be able to obtain the feature regardless of the orientation of a wire. The method first applies the Hough Transform to the surface projection of an object image from the ground penetrating radar, and then rotates the 3-D data image according to the orientation angle from the Hough Transform to align with the cross-track, before the extraction of ellipse feature. The proposed method is quite effective and provides high quality ellipse feature to aid the detection of wire in any orientation.
Wire detection is often based on line structure. This research investigates the use of ellipse feature to detect surface laid and shallowly buried wires. A wire has non-negligible diameter and elliptical shape appears in its cross-section image. After filtering and edge detection in the cross-section image, ellipse fitting is applied to obtain an ellipse feature for indicating how well the shape fits to an ellipse. Experimental results of the ellipse fitting technique are presented for the detection of wires and their discrimination with clutter objects.
This paper investigates the use of the Hough Transform (HT) for the detection of surface wires that are attached to explosives. Wires, when laid, have a linear structure in which HT can be a promising technique to extract the features and detect the wires. We use a step-frequency ground penetrating radar with a co-pole configuration mounted on an air-borne platform to collect the data for the research study. After beamforming for constructing the data image, projecting onto the surface plane and obtaining the edges, HT is applied to extract features for the detection of wire in the projected image. The features for wire detection include orientation, strength and relative strength that correspond to the tilt angle, the length and the confidence of a wire. Experimental results using the data collected from an indoor facility containing several kinds of wires show the effectiveness of HT for wire detection.
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