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长春光学精密机械与物... [4]
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会议论文 [4]
发表日期
2011 [4]
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发表日期:2011
专题:长春光学精密机械与物理研究所
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The sequence measurement system of the IR camera (EI CONFERENCE)
会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
Geng A.-H.
;
Han H.-X.
;
Zhang H.-B.
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浏览/下载:31/0
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提交时间:2013/03/25
Currently
the IR cameras are broadly used in the optic-electronic tracking
optic-electronic measuring
fire control and optic-electronic countermeasure field
but the output sequence of the most presently applied IR cameras in the project is complex and the giving sequence documents from the leave factory are not detailed. Aiming at the requirement that the continuous image transmission and image procession system need the detailed sequence of the IR cameras
the sequence measurement system of the IR camera is designed
and the detailed sequence measurement way of the applied IR camera is carried out. The FPGA programming combined with the SignalTap online observation way has been applied in the sequence measurement system
and the precise sequence of the IR camera's output signal has been achieved
the detailed document of the IR camera has been supplied to the continuous image transmission system
image processing system and etc. The sequence measurement system of the IR camera includes CameraLink input interface part
LVDS input interface part
FPGA part
CameraLink output interface part and etc
thereinto the FPGA part is the key composed part in the sequence measurement system. Both the video signal of the CmaeraLink style and the video signal of LVDS style can be accepted by the sequence measurement system
and because the image processing card and image memory card always use the CameraLink interface as its input interface style
the output signal style of the sequence measurement system has been designed into CameraLink interface. The sequence measurement system does the IR camera's sequence measurement work and meanwhile does the interface transmission work to some cameras. Inside the FPGA of the sequence measurement system
the sequence measurement program
the pixel clock modification
the SignalTap file configuration and the SignalTap online observation has been integrated to realize the precise measurement to the IR camera. Te sequence measurement program written by the verilog language combining the SignalTap tool on line observation can count the line numbers in one frame
pixel numbers in one line and meanwhile account the line offset and row offset of the image. Aiming at the complex sequence of the IR camera's output signal
the sequence measurement system of the IR camera accurately measures the sequence of the project applied camera
supplies the detailed sequence document to the continuous system such as image processing system and image transmission system and gives out the concrete parameters of the fval
lval
pixclk
line offset and row offset. The experiment shows that the sequence measurement system of the IR camera can get the precise sequence measurement result and works stably
laying foundation for the continuous system. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Design of control system of DC motor based on fusion FPGA (EI CONFERENCE)
会议论文
2011 International Conference on Mechatronics and Materials Processing, ICMMP 2011, November 18, 2011 - November 20, 2011, Guangzhou, China
Zhu D. D.
;
Li H. W.
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浏览/下载:29/0
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提交时间:2013/03/25
Along with the development of microelectronic process
it is possible to integrate a big system in one chip. A new way to implement system on a chip is provided by the advent of FPGA. Based on Verilog HDL and the Actel Fusion AFS600 FPGA chip
the speed closed-loop control system of DC motor was designed by using options of combining the top-down thinking and the bottom-up method. PID control algorithm
encoder signal processing and PWM waveform generation etc were realized by the system. The results show that the system structure is simplified and the stability and reliability are improved. A solution of system on a chip is realized to some extent. It has extensive application value in engineering practice. 2011 Trans Tech Publications.
The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE)
会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
Sun H.
;
Han H.-X.
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浏览/下载:50/0
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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).
Study of the neural network constitutive models for turfy soil with different decomposition degree (EI CONFERENCE)
会议论文
2011 2nd International Conference on Mechanic Automation and Control Engineering, MACE 2011, July 15, 2011 - July 17, 2011, Inner Mongolia, China
Lv Y.
;
Nie L.
;
Xu K.
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浏览/下载:16/0
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提交时间:2013/03/25
The turfy soil is of a special humus soil. The decomposition degree is the main factor on the physical and mechanical properties of turfy soil. To build the turfy soil constitutive model
there are a few shortages such as the calculation cumbersome and low accuracy for parameter value with the method of traditional models. Furthermore
those methods did not reflect the influence of strength that effected by decomposition degree of the turfy soil. In this paper
the relationship of stress-strain with different decomposition degrees of turfy soil was carried out through indoor tests. Based on above experimental results
an improved method
which divided into different zones according to different decomposition degrees of turfy soil and calculated combining with neural network constitutive model is put forward. The result shows that
the neural network of turfy soil has good fitting precision and good generalization ability. It can fully describe the influence of the turfy soil. 2011 IEEE.
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