中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
机构
采集方式
内容类型
发表日期
学科主题
筛选

浏览/检索结果: 共8条,第1-8条 帮助

条数/页: 排序方式:
Phylogenomics of Bivalvia Using Ultraconserved Elements Reveal New Topologies for Pteriomorphia and Imparidentia 期刊论文  OAI收割
SYSTEMATIC BIOLOGY, 2024, 页码: 18
作者:  
Li, Yi-Xuan;  Ip, Jack Chi-Ho
  |  收藏  |  浏览/下载:10/0  |  提交时间:2024/12/20
The research about high-dynamic and low-gray target image differential capture technology based on laser active detection 期刊论文  OAI收割
Eurasip Journal on Image and Video Processing, 2018, 卷号: 0, 页码: 15
作者:  
Chen, Z. B.;  Chen, N.;  Shi, K.;  Li, G. N.;  Liu, X. Y.
  |  收藏  |  浏览/下载:11/0  |  提交时间:2019/09/17
The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文  OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者:  
Sun H.;  Han H.-X.;  Sun H.
收藏  |  浏览/下载:59/0  |  提交时间:2013/03/25
Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring  precision  and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection  the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure  but in order to capture the change of the state space  it need a certain amount of particles to ensure samples is enough  and this number will increase in accompany with dimension and increase exponentially  this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining"  we expand the classic Mean Shift tracking framework.Based on the previous perspective  we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis  Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism  used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation  and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information  this approach also inhibit interference from the background  ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).  
Scanning program of image guided missile basing on parabolic trajectory (EI CONFERENCE) 会议论文  OAI收割
3rd IEEE International Conference on Advanced Computer Control, ICACC 2011, January 18, 2011 - January 20, 2011, Harbin, China
作者:  
Wang Y.;  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y.
收藏  |  浏览/下载:14/0  |  提交时间:2013/03/25
Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文  OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者:  
Dong Y.-X.;  Zhang H.-B.;  Li Y.;  Li Y.;  Li Y.
收藏  |  浏览/下载:111/0  |  提交时间:2013/03/25
Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system  the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms  such as adaptive background prediction detecting method. When background has dispersion-decreasing structure  the traditional target detection algorithms would be more useful. But when the background has large gray gradient  such as sea-sky-line  sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature  in our opinion  from the perspective of mathematics  the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis  the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection  its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore  the purpose of the image preprocessing is to reduce the effects from noise  also to raise the SNR of image  and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics  the median filter is used to eliminate noise  improve signal-to-noise ratio  then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line  so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).  
Station mode for attitude determination of small-multi-target with high speed (EI CONFERENCE) 会议论文  OAI收割
2010 International Conference on E-Product E-Service and E-Entertainment, ICEEE2010, November 7, 2010 - November 9, 2010, Henan, China
作者:  
Wang J.;  Zhao L.;  Li M.
收藏  |  浏览/下载:25/0  |  提交时间:2013/03/25
A key problem of attitude measurement of small-multi-target with high speed is how to decide the optimum of the CMOS stations. A multi-CMOS station mode is designed in this paper  multiple CMOS videos were placed on two parallel sides in measurement system  every two CMOS form an intersection viewing field  multiple viewing field join to cover shooting range  which can augment Effective Viewing Field(EVF)  increase capture ratio of objects with high speed and measurement precision of small objects. When an object passes through the joint area  it will be imaged separately on each CMOS focal plane. Multiple CMOS videos were triggered synchronously  a sequence of image information was extracted  the target attitude was confirmed by digital image processing technology. The merit of station mode is low cost  large measurement scope  extending freely and so on. 2010 IEEE.  
Research on tracking approach to low-flying weak small target near the sea (EI CONFERENCE) 会议论文  OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者:  
Xue X.-C.
收藏  |  浏览/下载:33/0  |  提交时间:2013/03/25
Automatic target detection is very difficult in complicate background of sea and sky because of the clutter caused by waves and clouds nearby the sea-level line. In this paper  in view of the low-flying target near the sea is always above the sea-level line  we can first locate the sea-level line  and neglect the image data beneath the sea-level line. Thus the noise under the sea-level line can be suppressed  and the executive time of target segmentation is also much reduced. A new method is proposed  which first uses neighborhood averaging method to suppress background and enhance targets so as to increase SNR  and then uses the multi-point multi-layer vertical Sobel operator combined with linear least squares fitting to locate the sea-level line  lastly uses the centroid tracking algorithm to detect and track the target. In the experiment  high frame rate and high-resolution digital CCD camera and high performance DSP are applied. Experimental results show that this method can efficiently locate the sea-level line on various conditions of lower contrast  and eliminate the negative impact of the clutter caused by waves and clouds  and capture and track target real-timely and accurately.  
Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文  OAI收割
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Sun J.; Ma D.
收藏  |  浏览/下载:27/0  |  提交时间:2013/03/25
The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task  for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type  the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP  but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly  we use frame grabber to capture the 4-bar target image data. Then according to image gray scale  we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets  along with known target visibility  are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm  demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.