This paper describes a novel inpainting approach for removing marked dynamic objects from videos captured with a camera, so long as the objects occlude parts of the scene with a static background. Proposed approach allow to remove objects or restore missing or tainted regions present in a video sequence by utilizing spatial and temporal information from neighboring scenes. The algorithm iteratively performs following operations: achieve frame; update the scene model; update positions of moving objects; replace parts of the frame occupied by the objects marked for remove with use of a background model. In this paper, we extend an image inpainting algorithm based texture and structure reconstruction by incorporating an improved strategy for video. An image inpainting approach based on the construction of a composite curve for the restoration of the edges of objects in a frame using the concepts of parametric and geometric continuity is presented. It is shown that this approach allows to restore the curved edges and provide more flexibility for curve design in damaged frame by interpolating the boundaries of objects by cubic splines. After edge restoration stage, a texture reconstruction using patch-based method is carried out. We demonstrate the performance of a new approach via several examples, showing the effectiveness of our algorithm and compared with state-of-the-art video inpainting methods.
A new promising architecture of microwave personnel screening system is analyzed in this paper with numerical simulations. This architecture is based on the concept of inverse aperture synthesis applied to a naturally moving person. The extent of the synthetic aperture is formed by a stationary vertical linear antenna array and by a length of subject’s trajectory as he moves in the vicinity of this antenna array. The coherent radar signal processing is achieved by a synchronous 3D video-sensor whose data are used to track the subject. The advantages of the proposed system architecture over currently existing systems are analyzed. Synthesized radar images are obtained by numerical simulations with a human torso model with concealed objects. Various aspects of the system architecture are considered, including: advantages of using sparse antenna arrays to decrease the number of antenna elements, the influence of positioning errors of body surface due to outer clothing. It was shown that detailed radar images of concealed objects can be obtained with a narrow-band signal due to the depth information available from the 3D video sensor. The considered ISAR architecture is considered perspective to be used on infrastructure objects owing to its superior qualities: highest throughput, small footprint, simple design of the radar sub-system, non-required co-operation of the subject.
KEYWORDS: Radar, Radar signal processing, Video, Signal processing, Sensors, Transceivers, Microwave radiation, Video processing, Scanners, Imaging systems
This paper describes the architecture of a microwave radar system intended for imaging concealed objects under clothing as a subject walks through the inspection area. The system uses the principle of inverse aperture which is achieved by a person’s movement past a stationary microwave sensor array. In the system, the vertical resolution is achieved by arranging microwave sensors vertically while the horizontal resolution is due to the subject’s horizontal motion. The positioning of the objects is achieved by employing a synchronous video sensor that allows coherent radar signal processing. A possible radar signal processing technique based on signal accumulation is described. Numerical experiments are conducted with the described object trajectory model. The influence of positioning errors attributed to the video positioning system is also modeled numerically. An experimental setup is designed and proposed to evaluate the suggested signal processing techniques on real data with an electro-mechanical scanner and single transceiver. It is suggested that the signal acquisition with the system can be accomplished using the stop motion technique, in which a series of changing stationary scenes is sampled and processed. Experimental radar images are demonstrated for stationary objects with concealed items and considered as reference images. Further development of the system is suggested.
In this paper, microwave holography is considered as a tool to obtain high resolution images of shallowly buried objects. Signal acquisition is performed at multiple frequencies on a grid using a two-dimensional mechanical scanner moving a single transceiver over an area of interest in close proximity to the surface. The described FFT-based reconstruction technique is used to obtain a stack of plan view images each using only one selected frequency from the operating waveband of the radar. The extent of a synthetically-formed aperture and the signal wavelength define the plan view resolution, which at sounding frequencies near 7 GHz amounts to 2 cm. The system has a short depth of focus which allows easy selection of proper focusing plane. The small distance from the buried objects to the antenna does not prevent recording of clean images due to multiple reflections (as happens with impulse radars). The description of the system hardware and signal processing technique is illustrated using experiments conducted in dry sand. The microwave images of inert anti-personnel mines are demonstrated as examples. The images allow target discrimination based on the same visually-discernible small features that a human observer would employ. The demonstrated technology shows promise for modification to meet the specific practical needs required for humanitarian demining or in multi-sensor survey systems.
A system for mine detection in aerial images is considered as an interactive system in which the operator is responsible
for making iterative queries to the database of images and analyzing the results. Preliminary, each image undergoes
formal decomposition into a set of feature vectors. Each feature vector is calculated for every irregularity found at a
scale-invariant salient point detection stage where a blob detector is used. Assuming that every small object in the image
can be described by a single invariant feature vector calculated on a patch around the salient point, formalization of
search algorithms is feasible. While the template-based search is straightforward in the terms of one object - one feature
vector, we focus on another important option when searching for mines - similar object search. For similar object search
a hierarchical clustering algorithm is considered. The mentioned steps of image processing as well as similar object
search are illustrated by performing on aerial mine field images taken by an electronic camera from a height of 27
meters. Encouraging preliminary results lead to the formulated plan for future research. The developed algorithms are
planned to be used in an image search engine allowing the operator to interactively search for mines in a database of
aerial images in humanitarian de-mining operations.
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