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Zhang D.,CAS Shenyang Institute of Automation | Zhang D.,University of Chinese Academy of Sciences | Zhang D.,Chinese Academy of Sciences | Zhang D.,Key Laboratory of Image Understanding and Computer Vision | And 7 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

Since the dome experiences the convective heat loading, thermal stress will be generated in the thickness direction. Thus, estimation of the thermal shock and analysis of the thermal shock resistance of the dome are the key to the design of the dome. In this paper, thermal shock resistance of CVD ZnS dome is analysed based on the flight condition of 6000m altitude and 3.0 Mach. We obtained the critical Reynolds number through a rockets pry experiment, which deduced that there exists a transition from laminar flow to turbulent flow at somewhere over the dome. We calculated the heat transfer coefficient over dome through heat transfer coefficient engineering formula of high-speed sphere with turbulent boundary layer near the stagnation point. The largest heat transfer coefficient is 2590W/(m2.K). Then, we calculated the transient thermal stress of dome by using the finite element method. Then we obtained the temperature and thermal stress distribution of different time through the direction of thickness. In order to obtain the mechanical properties of CVD ZnS at high temperatures, the 3-point bending method was used to test the flexure strength of CVD ZnS at different temperature. When compared the maximum thermal stress with flexure strength at different temperature, we find that the safety factors were not less than 1.75. The result implied that the dome has good safety margin under the proposed application condition. Through the above test and analysis, we can get the conclusion that the thermal shock resistance of the CVD ZnS dome satisfied the requirements of flight conditions. © 2016 SPIE.


Tan S.,CAS Shenyang Institute of Automation | Tan S.,University of Chinese Academy of Sciences | Tan S.,Chinese Academy of Sciences | Tan S.,Key Laboratory of Image Understanding and Computer Vision | And 7 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

Recently, Kernel Correlation Filter (KCF) has achieved great attention in visual tracking filed, which provide excellent tracking performance and high possessing speed. However, how to handle the scale variation is still an open problem. In this paper, focusing on this issue that a method based on Gaussian scale space is proposed. First, we will use KCF to estimate the location of the target, the context region which includes the target and its surrounding background will be the image to be matched. In order to get the matching image of a Gaussian scale space, image with Gaussian kernel convolution can be gotten. After getting the Gaussian scale space of the image to be matched, then, according to it to estimate target image under different scales. Combine with the scale parameter of scale space, for each corresponding scale image performing bilinear interpolation operation to change the size to simulate target imaging at different scales. Finally, matching the template with different size of images with different scales, use Mean Absolute Difference (MAD) as the match criterion. After getting the optimal matching in the image with the template, we will get the best zoom ratio s, consequently estimate the target size. In the experiments, compare with CSK, KCF etc. demonstrate that the proposed method achieves high improvement in accuracy, is an efficient algorithm. © 2016 SPIE.


Zhang D.,CAS Shenyang Institute of Automation | Zhang D.,University of Chinese Academy of Sciences | Zhang D.,Chinese Academy of Sciences | Zhang D.,Key Laboratory of Image Understanding and Computer Vision | And 7 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

For the optical guidance system flying at low altitude and high speed, the calculation of turbulent convection heat transfer over its dome is the key to designing this kind of aircraft. RANS equations-based turbulence models are of high computation efficiency and their calculation accuracy can satisfy the engineering requirement. But for the calculation of the flow in the shock layer of strong entropy and pressure disturbances existence, especially of aerodynamic heat, some parameters in the RANS energy equation are necessary to be modified. In this paper, we applied turbulence models on the calculation of the heat flux over the dome of sphere-cone body at zero attack. Based on Billig's results, the shape and position of detached shock were extracted in flow field using multi-block structured grid. The thermal conductivity of the inflow was set to kinetic theory model with respect to temperature. When compared with Klein's engineering formula at the stagnation point, we found that the results of turbulent models were larger. By analysis, we found that the main reason of larger values was the interference from entropy layer to boundary layer. Then thermal conductivity of inflow was assigned a fixed value as equivalent thermal conductivity in order to compensate the overestimate of the turbulent kinetic energy. Based on the SST model, numerical experiments showed that the value of equivalent thermal conductivity was only related with the Mach number. The proposed modification approach of equivalent thermal conductivity for inflow in this paper could also be applied to other turbulence models. © 2016 SPIE.


Zhang L.,CAS Shenyang Institute of Automation | Zhang L.,University of Chinese Academy of Sciences | Zhu F.,CAS Shenyang Institute of Automation | Zhu F.,Chinese Academy of Sciences | And 4 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

In order to enable the non-cooperative rendezvous, capture, and removal of large space debris, robust and fast tracking of the non-cooperative target is needed. This paper proposes an improved algorithm of real-time visual tracking for space non-cooperative target based on three-dimensional model, and it does not require any artificial markers. The non-cooperative target is assumed to be a 3D model known and constantly in the field of view of the camera mounted on the chaser. Space non-cooperative targets are regarded as less textured manmade objects, and the design documents of 3D model are available. Space appears to be black, so we can assume the object is in empty space and only the object is visible, and the background of the image is dark. Due to edge features offer a good invariance to illumination changes or image noise, our method relies on monocular vision and uses 3D-2D correspondences between the 3D model and its corresponding 2D edges in the image. The paper proposes to remove the sample points that are susceptible to false matches based on geometrical distance due to perspective projection of the 3D model. To allow a better robustness, we compare the local region similarity to get better matches between sample points and edge points. Our algorithm is proved to be efficient and shows improved accuracy without significant computational burden. The results show potential tracking performance with mean errors of < 3 degrees and < 1.5% of range. © 2016 SPIE.


Luo H.,CAS Shenyang Institute of Automation | Luo H.,Chinese Academy of Sciences | Luo H.,Key Laboratory of Image Understanding and Computer Vision | Chang Z.,CAS Shenyang Institute of Automation | And 5 more authors.
Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering | Year: 2011

Target tracking with local non-texture is a difficult point and hot topic in the field of ground imaging guidance. Since the automatic suitable-matching area selection is an effective method to solve this problem, an algorithm of automatic suitable-matching area selection based on multi-feature fusion was proposed. Firstly, the edge density, the average edge strength, the edge direction dispersion degree and the space distance were integrated to form a suitable-matching measure function. Then, the credibility of suitable-matching of each point in the image was calculated by this function. Lastly, through developing adaptive selection strategy to the suitable-matching area, three suitable-matching areas with high credibility were segmented as target template for matching tracking. Experimental results show that the segmented suitable-matching area with proposed algorithm can achieve more tracking precision compared with the results judged by the human experience. This proposed algorithm can be widely used in the applications of the ground imaging-guided target tracking with local non-texture target and the scene matching task planning.


Liu Y.,CAS Shenyang Institute of Automation | Liu Y.,University of Chinese Academy of Sciences | Liu Y.,Chinese Academy of Sciences | Liu Y.,Key Laboratory of Image Understanding and Computer Vision | And 3 more authors.
Eurasip Journal on Advances in Signal Processing | Year: 2010

Region covariance descriptor recently proposed has been approved robust and elegant to describe a region of interest, which has been applied to visual tracking. We develop a geometric method for visual tracking, in which region covariance is used to model objects appearance; then tracking is led by implementing the particle filter with the constraint that the system state lies in a low dimensional manifold: affine Lie group. The sequential Bayesian updating consists of drawing state samples while moving on the manifold geodesics; the region covariance is updated using a novel approach in a Riemannian space. Our main contribution is developing a general particle filtering-based racking algorithm that explicitly take the geometry of affine Lie groups into consideration in deriving the state equation on Lie groups. Theoretic analysis and experimental evaluations demonstrate the promise and effectiveness of the proposed tracking method. Copyright © 2010 Yunpeng Liu et al.


Dong S.,CAS Shenyang Institute of Automation | Dong S.,University of Chinese Academy of Sciences | Dong S.,Chinese Academy of Sciences | Dong S.,Key Laboratory of Image Understanding and Computer Vision | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2015

A high dynamic range infrared image of the sea surface scene includes the effects due to the sea clutter, mirror reflections from the wave facets, which decrease the visibility of the ship targets and their details. This paper provides an efficient adaptive enhancement technique for ship targets based on bilateral filtering and visual saliency detection. The 14- bit raw image is separated into a detail layer and a base layer by applying an adaptive bilateral filter. Then the two layers are processed separately and added afterward. Hereafter by employing visual saliency detection we can get the gain matrix to improve the contrast of ship targets. Finally, the image whose contrast is improved is quantized to the display range. The strength of our proposed method lies in its ability to inhibit the sea clutter and adaptability in different sea surface scene and shows a better performance in the contrast of the ship targets and the visibility of their details. © 2015 SPIE.


Chen H.,CAS Shenyang Institute of Automation | Chen H.,University of Chinese Academy of Sciences | Chen H.,Chinese Academy of Sciences | Chen H.,Key Laboratory of Image Understanding and Computer Vision | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2015

With the development of modern military, infrared imaging technology is widely used in this field. However, limited by the mechanism of infrared imaging and the detector, infrared images have the disadvantages of low contrast and blurry edge by comparison with the visible image. These shortcomings lead infrared image unsuitable to be observed by both human and computer. Thus image enhancement is required. Traditional image enhancement methods on the application of infrared image, without taking into account the human visual properties, is not convenient for the human observation. This article purposes a new method that combines the layering idea with the human visual properties to enhance the infrared image. The proposed method relies on bilateral filtering to separate a base component, which contains the large amplitude signal and must be compressed, from a detail component, which must be expanded because it contains the small signal variations related to fine texture. The base component is mapped into the proper range which is 8-bit using the human visual properties, and the detail component is applied the method of adaptive gain control. Finally, the two parts are recombined and quantized to 8-bit domain. Experimental results show that this algorithm exceeds most current image enhancement methods in solving the problems of low contrast and blurry detail. © 2015 SPIE.


Xu B.,CAS Shenyang Institute of Automation | Xu B.,University of Chinese Academy of Sciences | Xu B.,Chinese Academy of Sciences | Xu B.,Key Laboratory of Image Understanding and Computer Vision | And 7 more authors.
Guangxue Xuebao/Acta Optica Sinica | Year: 2011

Modulation transfer function (MTF) is one of significant parameters for designing and evaluating an electro-optical imaging system. By proving the linear relation between an edge spread function and an inverse cumulative histogram of edge, an MTF measurement method based on statistical histogram is presented. Simulation and experiment including optics and detectors are designed. Physical experimental platform including an integrating sphere, target, collimator, digital camera and other devices is developed. Taking the theoretical model and design parameters of electro-optical imaging system as a reference, the validity of our measurement method is verified by the simulation and experiment. Experimental results indicate that, comparing with the existing MTF measurement method, the proposed method can overcome the phase effects which is caused by under-sampling of imaging detector. It is more robust to angle of knife edge and noisy environment, and can measure response properties beyond the sampling frequency of an electro-optical imaging system.


Ma J.,CAS Shenyang Institute of Automation | Luo H.,University of Chinese Academy of Sciences | Chang Z.,Chinese Academy of Sciences | Hui B.,Key Laboratory of Image Understanding and Computer Vision
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

In this paper, we propose a robust tracking method for infrared object. We introduce the appearance model and the sparse representation in the framework of particle filter to achieve this goal. Representing every candidate image patch as a linear combination of bases in the subspace which is spanned by the target templates is the mechanism behind this method. The natural property, that if the candidate image patch is the target so the coefficient vector must be sparse, can ensure our algorithm successfully. Firstly, the target must be indicated manually in the first frame of the video, then construct the dictionary using the appearance model of the target templates. Secondly, the candidate image patches are selected in following frames and the sparse coefficient vectors of them are calculated via ℓ1-norm minimization algorithm. According to the sparse coefficient vectors the right candidates is determined as the target. Finally, the target templates update dynamically to cope with appearance change in the tracking process. This paper also addresses the problem of scale changing and the rotation of the target occurring in tracking. Theoretic analysis and experimental results show that the proposed algorithm is effective and robust. © 2014 SPIE.

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