Camouflaged Targets Research Articles

Second-order cues to figure motion enable object detection during prey capture by praying mantises

Detecting motion is essential for animals to perform a wide variety of functions. In order to do so, animals could exploit motion cues, including both first-order cues-such as luminance correlation over time-and second-order cues, by correlating higher-order visual statistics. Since first-order motion cues are typically sufficient for motion detection, it is unclear why sensitivity to second-order motion has evolved in animals, including insects. Here, we investigate the role of second-order motion in prey capture by praying mantises. We show that prey detection uses second-order motion cues to detect figure motion. We further present a model of prey detection based on second-order motion sensitivity, resulting from a layer of position detectors feeding into a second layer of elementary-motion detectors. Mantis stereopsis, in contrast, does not require figure motion and is explained by a simpler model that uses only the first layer in both eyes. Second-order motion cues thus enable prey motion to be detected, even when perfectly matching the average background luminance and independent of the elementary motion of any parts of the prey. Subsequent to prey detection, processes such as stereopsis could work to determine the distance to the prey. We thus demonstrate how second-order motion mechanisms enable ecologically relevant behavior such as detecting camouflaged targets for other visual functions including stereopsis and target tracking.

Research on broadband tunable metamaterial absorber based on PIN diode

Radar absorbing materials (RAMs) have been widely applied in the fields of electromagnetic shielding and target camouflage. The current radar absorbing materials are passive, and the frequency response and absorption features are fixed as soon as they are prepared, which limits their further application in the future. In this work, a sort of state-of-the-art broadband tunable radar absorber is designed, fabricated and measured. The active metamaterial absorber and passive absorbing honeycomb are creatively combined together to achieve the overall absorptance of less than -10 dB in frequency range of 7˜22 GHz. Furthermore, PIN diodes are introduced into the metamaterial radar absorber. By adjusting the bias voltage of the PIN diode array, the radar absorbing property can be actively tuned in a wide frequency range in the condition of broadband and high efficiency absorption.

Design of an acoustic illusion device based on a shifting medium and multi-folded transformation.

An acoustic illusion device that can act as an invisible cloak or a shifting medium depending on the value of shift distance, which is about twice the circum-radius of the outer polygon, is proposed and designed based on linear coordinate transformation. A multi-folded transformation approach is used to design an illusion device with a circular opening window that allows for information interaction with the outside world. The results show that the proposed device can hide objects with arbitrary shapes or positions. Furthermore, in order to remove the material anisotropy of the proposed illusion device, a layered structure composed of homogenous and isotropic material is used based on the effective medium theory. The combination of the layered structure and the circular opening provide a flexible and feasible approach to achieve the partial implementation of the illusion device. It is hoped that these results may open an avenue for designing and implementing invisibility cloaks or illusion devices, and speed up potential applications for noise shielding, target camouflage, or target protection from active sonar signals.

基于深度神经网络的迷彩目标发现仿真学习方法

基于深度神经网络的迷彩目标发现仿真学习方法

Design and implementation of underwater laser imaging test aquarium

A test aquarium was built to perform and simulate different marine environment to optimize laser imaging of submerged targets. The setup can be used to study many parameters as required (i.e., the correlation between the detection angle, the target surface topology and color, water turbidity due to clay and mud, and laser type at different depths, and backgrounds). A theoretical model of the detection process was tested using MATLAB simulation. The system was able to simulate light extinction of the real deep and shallow aqua environments due to plankton chlorophyll. The used dummy targets are approximately 1/500 of the real submarines and naval mines. These targets were illuminated by several laser wavelengths in order to identify the targets with different color and shapes. The setup permits to test the efficiency of different target camouflage versus optical detection.

Modeling apparent camouflage-pattern color using segment-weighted spectra

ABSTRACTCamouflage patterns for military applications, typically upon base materials such as dyed fabrics, consist of highly detailed camouflage patternings that are characterized by combined refectance spectra. The complexity of these camouflage patterns establishes a need for modeling camouflage-pattern reflectance for pattern evaluation as a function of distance. A metric for pattern evaluation is the apparent-camouflage-pattern reflectance spectrum, which is the total reflectance due to all contributions from component segments, within a wavelength range of interest, for light reflected from sufficiently large fabric samples (≥1m2), as a function of standoff distance. This follows in that camouflage patterns tend to lose contributions to the total reflectance from component segments, having less coverage, with increasing standoff distance. Eventually, with increasing distance, reflectance of pattern segments having more coverage combine to produce the “apparent spectrum” of the camouflage pattern at far field. The physical characteristics of camouflage-pattern reflectance spectra are based on far-field and diffuse scattering properties of electromagnetic waves. Accordingly, a modeling approach can be developed to simulate camouflage-pattern spectra using diffuse-reflectance theory, which is based on decomposition of camouflage-pattern reflectance with respect to component segments of camouflage patterns. This paper presents a modeling approach and prototype simulations of camouflage-pattern reflectance within the visible range of wavelengths, which are relevant for evaluating camouflage fabrics with respect to realistic field conditions. A significant aspect of this modeling approach is that it can be extended for simulation of a wide range of factors influencing detection of camouflaged targets.

Detection and Identification of Camouflaged Targets using Hyperspectral and LiDAR data

<p class="p1">Camouflaging is the process of merging the target with the background with the aim to reduce/delay its detection. It can be done using different materials/methods such as camouflaging nets, paints. Defence applications often require quick detection of camouflaged targets in a dynamic battlefield scenario. Though HSI data may facilitate detection of camouflaged targets but detection gets complicated due to issues (spectral variability, dimensionality). This paper presents a framework for detection of camouflaged target that allows military analysts to coordinate and utilise the expert knowledge for resolving camouflaged targets using remotely sensed data. Desired camouflaged target (set of three chairs as a target under a camouflaging net) has been resolved in three steps: First, hyperspectral data processing helps to detect the locations of potential camouflaged targets. It narrows down the location of the potential camouflaged targets by detecting camouflaging net using Independent component analysis and spectral matching algorithms. Second, detection and identification have been performed using LiDAR point cloud classification and morphological analysis. HSI processing helps to discard the redundant majority of LiDAR point clouds and support detailed analysis of only the minute portion of the point cloud data the system deems relevant. This facilitates extraction of salient features of the potential camouflaged target. Lastly, the decisions obtained have been fused to infer the identity of the desired targets. The experimental results indicate that the proposed approach may be used to successfully resolve camouflaged target assuming some <em>a priori </em>knowledge about the morphology of targets likely to be present.<span class="Apple-converted-space"> </span></p>

Camouflage Effectiveness Assessment Based on Fusion with Constant Color Background

In the constant-color background, the structure feature is more influential in evaluation of the target camouflage effectiveness its surface is covered by the color that matches the background compared with the color feature. Against this, a method fusing the index of similarity and the index of difference is proposed. The index of similarity is designed based on texture, orientation and intensity features and described by saliency maps. The index of difference is designed based on target’s own feature of straight-section edge and described by the weighted maximum entropy principle. These two features are fused to evaluate the camouflage effect. Experimental results show that our camouflage evaluation framework accords with the human visual perception mechanism.

Dissociating the effect of disruptive colouration on localisation and identification of camouflaged targets

Disruptive camouflage features contrasting areas of pigmentation across the animals’ surface that form false edges which disguise the shape of the body and impede detection. In many taxa these false edges feature local contrast enhancement or edge enhancement, light areas have lighter edges and dark areas have darker edges. This additional quality is often overlooked in existing research. Here we ask whether disruptive camouflage can have benefits above and beyond concealing location. Using a novel paradigm, we dissociate the time courses of localisation and identification of a target in a single experiment. We measured the display times required for a stimulus to be located or identified (the critical duration). Targets featured either uniform, disruptive or edge enhanced disruptive colouration. Critical durations were longer for identifying targets with edge enhanced disruptive colouration camouflage even when presented against a contrasting background, such that all target types were located equally quickly. For the first time, we establish empirically that disruptive camouflage not only conceals location, but also disguises identity. This shows that this form of camouflage can be useful even when animals are not hidden. Our findings offer insights into how edge enhanced disruptive colouration undermines visual perception by disrupting object recognition.

The Design and Implementation of Under-Water Laser Imaging Test Aquarium

A test aquarium was built to perform and simulate different marine environment to optimize laser imaging of submerged targets. The setup enable to study the correlation between the detection angle, the target surface topology and color, water turbidity, and laser type at different depths and backgrounds. A theoretical model of the detection process was tested using MATLAB simulation. The system was able to simulate light extinction of the real deep and shallow aqua environments due to plankton chlorophyll as well as the effect of clay and mud water turbidity. The used dummy targets are approximately 1/500 of the real submarines and naval mines. These targets were illuminated by several laser wavelengths in order to identify the targets with different color and shapes. The setup permits to test the efficiency of different target camouflage versus optical detection.

Impulse response measurement in the HgCdTe avalanche photodiode

HgCdTe based mid-wave infrared focal plane arrays (MWIR FPAs) are being developed for high resolution imaging and range determination of distant camouflaged targets. Effect of bandgap grading on the response time in the n+/ν/p+ HgCdTe electron avalanche photodiode (e-APD) is evaluated using impulse response measurement. Gain normalized dark current density of 2 × 10−9 A/cm2 at low reverse bias for passive mode and 2 × 10−4 A/cm2 at −8 V for active mode is measured in the fabricated APD device, yielding high gain bandwidth product of 2.4 THZ at the maximum gain. Diffusion of carriers is minimized to achieve transit time limited impulse response by introducing composition grading in the HgCdTe epilayer. The noise equivalent photon performance less than one is achievable in the FPA that is suitable for active cum passive imaging applications.

FOV Expansion of Bioinspired Multiband Polarimetric Imagers With Convolutional Neural Networks

Spectral and polarimetric contents of the light reflected from an object contain useful information on material type and surface characteristics of the object. Jointly exploiting spatial, spectral, and polarimetric information helps detect camouflage targets. Motivated by the vision mechanism of some known aquatic insects, we construct a bioinspired multiband polarimetric imaging system using a camera array, which simultaneously captures multiple images of different spectral bands and polarimetric angles. But the disparity between the fixed positions of each component camera leads to the loss of information in the boundary region and a reduction in the field of view (FOV). In order to overcome the limits, this paper presents a deep learning method for FOV expansion, incorporating the gradient prior of the image into a nine-dimensional convolutional neural network's framework to learn end-to-end mapping between the incomplete images and the FOV-expanded images. With FOV expansion, the proposed model recovers significant missing information. For the problem of insufficient training data, we construct the training dataset and propose the corresponding training methods to achieve good convergence of the network. We also provide some experimental results to validate its state-of-the-art performance of FOV expansion.

Research on Camouflage Target Detection via Computational Analysis with Spectral Imaging

Camouflage target detection is one of most important techniques in a great number of applications such as remote sensing, security monitoring and industrial production. In this paper, high-resolution spectral imaging together with computational analysis on spectral data cube is adopted to solve camouflage target recognition problem. Spectral data cubes of certain experimental scene are collected by a self-developed visual-band imaging spectrometer, and spectral information divergence (SID) is adopted as difference descriptor to discriminate abnormal target. SIDs of the whole spectral region and several specific ranges are all measured to quantitatively evaluate the effort of band selection on camouflage detection. This is proven to be a low-cost and effective tool for camouflage target detection and can be further developed beyond visual band spectral imaging technique.

Calculation model of scattering depolarization for camouflaged target detection system

As a new physical model to identify the camouflaged targets in the complex environments, the main effect of the polarization measurement system is the scattering depolarization information of different measured parts. This paper had observed the multiple scattering theory of electromagnetic wave, and analyzed the mechanism of the relation between the depolarization and scattering path. The correctness and accuracy of the theoretical model had been verified by the Fresnel formula. In order to prove the practicability of this model, the experiments on two kinds of camouflage materials had been conducted at seven different angles. Research shows that, as a link between material physical characteristics and optical signal information, the model could accurately and effectively identify the moving camouflaged objects. Therefore, this method has a great application value, and the paper has very important significance on the development of tracking technology.

Long-range depth profiling of camouflaged targets using single-photon detection

We investigate the reconstruction of depth and intensity profiles from data acquired using a custom-designed time-of-flight scanning transceiver based on the time-correlated single-photon counting technique. The system had an operational wavelength of 1550 nm and used a Peltier-cooled InGaAs/InP single-photon avalanche diode detector. Measurements were made of human figures, in plain view and obscured by camouflage netting, from a stand-off distance of 230 m in daylight using only submilliwatt average optical powers. These measurements were analyzed using a pixelwise cross correlation approach and compared to analysis using a bespoke algorithm designed for the restoration of multilayered three-dimensional light detection and ranging images. This algorithm is based on the optimization of a convex cost function composed of a data fidelity term and regularization terms, and the results obtained show that it achieves significant improvements in image quality for multidepth scenarios and for reduced acquisition times.

The Grass isn't Greener: No detriment for red-green color deficiency in search for camouflaged targets

The Grass isn't Greener: No detriment for red-green color deficiency in search for camouflaged targets

Breaking camouflage and detecting targets require optic flow and image structure information.

Use of motion to break camouflage extends back to the Cambrian [In the Blink of an Eye: How Vision Sparked the Big Bang of Evolution (New York Basic Books, 2003)]. We investigated the ability to break camouflage and continue to see camouflaged targets after motion stops. This is crucial for the survival of hunting predators. With camouflage, visual targets and distracters cannot be distinguished using only static image structure (i.e., appearance). Motion generates another source of optical information, optic flow, which breaks camouflage and specifies target locations. Optic flow calibrates image structure with respect to spatial relations among targets and distracters, and calibrated image structure makes previously camouflaged targets perceptible in a temporally stable fashion after motion stops. We investigated this proposal using laboratory experiments and compared how many camouflaged targets were identified either with optic flow information alone or with combined optic flow and image structure information. Our results show that the combination of motion-generated optic flow and target-projected image structure information yielded efficient and stable perception of camouflaged targets.

RETRACTED: Camouflage texture design based on its camouflage performance evaluation

Along with the development of the technique in camouflage design, camouflage design and evaluation methods have attracted much attention by researchers. Most of traditional methods of camouflage texture effect evaluation are subjective method. It is very tedious and inconvenient to evaluate the camouflage pattern using the artificial method. In this paper, a systemic and rational method for camouflage texture design based on camouflage evaluation feedback is proposed. In our model, two different types of features was selected to make a comprehensive evaluation on a given digital camouflage. First, we applied visual saliency technique to evaluate camouflage performance. Digital camouflage itself has some special properties, such as camouflage histogram feature, rectangular feature and mosaic feature, which can well describe the differences between the camouflaged targets and the background. Then, the two kinds of features are fused to evaluate the camouflage performance using a nonlinear fusion function. Experimental results show that our method accords with the human visual perception mechanism, and is helpful for evaluation and design of the camouflage texture. The proposed approach can not only calculate the camouflage performance, but also optimize the process of digital camouflage design as a feedback mechanism.

红外偏振成像系统高速处理模块设计

The high speed imaging processing module based on MWIR cooled 320256 detector, SDRAM memory and other function module circuit was designed for time-sharing type polarization imaging system. Processing module mainly included the driver board connected to detector, processing board with FPGA as its core, system power supply board. The algorithm of blind pixels compensation, nonuniformity correction, plateau histogram equalization and linear mapping were implemented, calibration parameters can be calculated online. Image processing module can realize the synchronization switch, integral time adjusted continuously, frame rate up to 200 fps, and output 320256 pixels high quality infrared image, meeting the requirement of the polarization imaging system to detect moving objects. Infrared polarization imaging experiments on plastic cups with groove were carried out, effective Stokes parameter images were extracted from the polarization images, and the significant polarization properties were observed. The processing module can be applied to the detection of space target, mine detection, maritime search and camouflage target detection.

Investigation of terahertz waves propagating through far infrared/CO2 laser stealth-compatible coating based on one-dimensional photonic crystal

We propose a new method to disclose the camouflaged targets coated with far infrared/CO2 laser stealth-compatible coating by utilizing terahertz (THz) radar. A coating based on one-dimensional photonic crystal (1DPC) with a defect mode is specially designed and successfully prepared, which possesses a high reflectivity in 8–14μm waveband and a low reflectivity at 10.6μm, by alternating thin films of Ge, ZnSe and Si. The propagation characteristic of 0.3–2THz wave at incident angle from 0° to 80° in such PC coating is investigated theoretically based on characteristic matrix method. The maximal transmittance is up to 92%, and the absorptivity keeps lower than 0.5% over the whole band. The results are verified by experiments, which demonstrate the feasibility of using THz radar to detect the targets covered with such stealth-compatible coatings.