中国科学院机构知识库网格系统: 检索

The ship-borne infrared searching and tracking system based on the inertial platform (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: Li Y.; Zhang H.; Zhang H.; Li Y.; Li Y.

收藏 | 浏览/下载：40/0 | 提交时间：2013/03/25

As a result of the radar system got interferenced or in the state of half silent it can cause the guided precision drop badly In the modern electronic warfare therefore it can lead to the equipment depended on electronic guidance cannot strike the incoming goals exactly. It will need to rely on optoelectronic devices to make up for its shortcomings but when interference is in the process of radar leading especially the electro-optical equipment is influenced by the roll pitch and yaw rotation it can affect the target appear outside of the field of optoelectronic devices for a long time so the infrared optoelectronic equipment can not exert the superiority and also it cannot get across weapon-control system "reverse bring" missile against incoming goals. So the conventional ship-borne infrared system unable to track the target of incoming quickly the ability of optoelectronic rivalry declines heavily.Here we provide a brand new controlling algorithm for the semi-automatic searching and infrared tracking based on inertial navigation platform. Now it is applying well in our XX infrared optoelectronic searching and tracking system. The algorithm is mainly divided into two steps: The artificial mode turns into auto-searching when the deviation of guide exceeds the current scene under the course of leading for radar.When the threshold value of the image picked-up is satisfied by the contrast of the target in the searching scene the speed computed by using the CA model Least Square Method feeds back to the speed loop. And then combine the infrared information to accomplish the closed-loop control of the infrared optoelectronic system tracking. The algorithm is verified via experiment. Target capturing distance is 22.3 kilometers on the great lead deviation by using the algorithm. But without using the algorithm the capturing distance declines 12 kilometers. The algorithm advances the ability of infrared optoelectronic rivalry and declines the target capturing time by using semi-automatic searching and reliable capturing-tracking when the lead deviation of the radar is great. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

An automatic pedestrian detection and tracking method: Based on mach and particle filter (EI CONFERENCE) 会议论文 OAI收割
2011 International Conference on Network Computing and Information Security, NCIS 2011, May 14, 2011 - May 15, 2011, Guilin, Guangxi, China
Han Q.; Yao Z.

收藏 | 浏览/下载：16/0 | 提交时间：2013/03/25

This paper introduces a pedestrian detecting and tracking approach. Correlation filters present the composite properties which have been successively used in target detection. Particle filter are combined to locate the targets in real-time. Our contribution is proposing a general algorithm that is able to detect and track pedestrians in clutter environments. We also create a different view pedestrian dataset. Experiments show our algorithm is comparative when there is block and occlusion in tracking. 2011 IEEE.

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).

Memoryless polynomial RLS adaptive filter for trajectory target tracking (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer Modeling and Simulation, ICCMS 2010, January 22, 2010 - January 24, 2010, Sanya, China
作者: Liu J.; Liu J.; Liu J.

收藏 | 浏览/下载：23/0 | 提交时间：2013/03/25

In order to find an effective solution to trajectory target tracking a memoryless polynomial adaptive filter is proposed in this paper. Unlike Volterra adaptive filter the proposed memoryless polynomial filter is composed of different monomials which can fit orbit trajectory very well. Besides the memoryless polynomial filter can be separated into a linearization filter and a transversal filter. Analogous to linear RLS adaptive filter a RLS adaptive filter is derived from the memoryless polynomial filter called Memoryless polynomial RLS adaptive filter (MLPRLS adaptive filter). Experiments show that the proposed filters have better performance than that of normal RLS filters in trajectory tracking. 2010 IEEE.

The application of TMS320c64x DSP assembly language in correlation tracking algorithms (EI CONFERENCE) 会议论文 OAI收割
2010 3rd International Congress on Image and Signal Processing, CISP 2010, October 16, 2010 - October 18, 2010, Yantai, China
Huang D.; Wu Z.; Liang M.; Dong Y.; Peng T.

收藏 | 浏览/下载：20/0 | 提交时间：2013/03/25

In order to improve the real-time performance of the conventional correlation tracking algorithm based on full search method for its huge computation amount and vast correlation matching times in the process of searching an optimal matching position a method of combining the TMS320C64x DSP assembly language and software pipelining is proposed to realize template matching which costs the most time of the algorithm. Choose high performance DSP chip TMS320DM642 as the core processor of the hardware platform and schedule each one of the instruction in the algorithm to maximize performance using the instruction-level parallelism of the DSP. The experimental results indicate the time of template image matching implemented in assembly language has decreased from 49.36ms to 0.62ms. It is concluded that the correlation tracking adopting proposed method can meet the real-time and stability requirement of the target tracking. 2010 IEEE.

Study on color image tracking and detection algorithms based on particle filter (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, June 17, 2009 - June 19, 2009, Beijing, China
Wu C.; Sun H.-J.; Yang D.

收藏 | 浏览/下载：20/0 | 提交时间：2013/03/25

In Video tracking detection and tracking need two algorithms. The process is complex and need much time which detection and tracking is. In this paper a hybrid valued sequential state vector is formulated. The state vector is characterized by information of target appearance and of location. Particle filter-based method implements detection and tracking. In order to reduce process time and think of pixel position in tracking field feature histogram of color-based is as observe vector and used posterior estimate. The experimental results confirm that method can detect and track object in 17.68ms successfully when the number of particles is 160. The method is robust for rolling scale and partial occlusion. 2009 SPIE.

High-accuracy real-time automatic thresholding for centroid tracker (EI CONFERENCE) 会议论文 OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Zhang Y.

收藏 | 浏览/下载：37/0 | 提交时间：2013/03/25

Many of the video image trackers today use the centroid as the tracking point. In engineering we can get several key pairs of peaks which can include the target and the background around it and use the method of Otsu to get intensity thresholds from them. According to the thresholds it give a great help for us to get a glancing size a target's centroid is computed from a binary image to reduce the processing time. Hence thresholding of gray level image to binary image is a decisive step in centroid tracking. How to choose the feat thresholds in clutter is still an intractability problem unsolved today. This paper introduces a high-accuracy real-time automatic thresholding method for centroid tracker. It works well for variety types of target tracking in clutter. The core of this method is to get the entire information contained in the histogram we can gain the binary image and get the centroid from it. To track the target so that we can compare the size of the object in the current frame with the former. If the change is little such as the number of the peaks the paper also suggests subjoining an eyeshot-window we consider the object has been tracked well. Otherwise their height just like our eyes focus on a target if the change is bigger than usual position and other properties in the histogram. Combine with this histogram analysis we will not miss it unless it is out of our eyeshot we should analyze the inflection in the histogram to find out what happened to the object. In general the impression will help us to extract the target in clutter and track it and we will wait its emergence since it has been covered. To obtain the impression what we have to do is turning the analysis into codes for the tracker to determine a feat threshold. The paper will show the steps in detail. The paper also discusses the hardware architecture which can meet the speed requirement. the paper offers a idea comes from the method of Snakes

Adaptive Image Segmentation based on Fast Thresholding and Image Merging (EI CONFERENCE) 会议论文 OAI收割
16th International Conference on Artificial Reality and Telexistence - Workshops, ICAT 2006, November 29, 2006 - December 1, 2006, Hangzhou, China
作者: Zhang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.

收藏 | 浏览/下载：14/0 | 提交时间：2013/03/25

Image segmentation is the first essential and important step of low level vision. This paper proposes a novel algorithm for adaptive image segmentation it can be applied in many conditions based on thresholding technique and segments merging according to their characteristics combine with spatial position. Our earlier work of getting the entire information of the histogram could help choose the multiple thresholds. However including complex target segmented. We describe the algorithm in detail and perform simulation experiments. The computation based on pixels can fully parallel processing to save time. 2006 IEEE. not all the peaks of the histogram correspond to obvious structural unit in the image. Spatial information must be involved. This paper also suggests subjoining segments matching for video image tracking. They will give great help to image segmentation. The proposed algorithm can meet the real-time requirement and lead to higher segmentation accuracy some types of texture can also be segmented well

A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文 OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者: Yao Z.-J.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However 3. applying the standard Hough transform equation to every point of the input image edge 4. according to the local threshold 6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes traditional Hough transform can only detect the lines 2. quantizing the parameter space and extracting a group of maximums according to the global threshold eliminating spurious peaks which are caused by the spreading effects and will improve the precision of tracking. cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately 5. fixing on the endpoints of the segments according to the dynamic clustering rule which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image parameter and line-segment spaces

Auction-based dynamic coalition for single target tracking in wireless sensor networks 会议论文 OAI收割
6th World Congress on Intelligent Control and Automation, Dalian, China, June 21-23, 2006
作者: Chen JX(陈剑霞); Zang CZ(臧传治); Liang W(梁炜); Yu HB(于海斌)

收藏 | 浏览/下载：26/0 | 提交时间：2012/06/06

wireless sensor networks target tracking. auction-based dynamic coalition task allocation