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长春光学精密机械与物... [3]
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会议论文 [2]
期刊论文 [1]
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2011 [1]
2006 [2]
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专题:长春光学精密机械与物理研究所
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Robust control of quadrotor MAV using self-organizing interval type-II fuzzy neural networks (SOIT-IIFNNs) controller
期刊论文
International Journal of Intelligent Computing and Cybernetics, 2011, 卷号: 4, 期号: 3, 页码: 397-412
Chen X.
;
Li D.
;
Xu Z.
;
Bai Y.
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  |  
浏览/下载:11/0
  |  
提交时间:2013/03/27
Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE)
会议论文
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Sun J.
;
Ma D.
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  |  
浏览/下载:17/0
  |  
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.
An object recognition method based on fuzzy theory and BP networks (EI CONFERENCE)
会议论文
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
Chuan W.
;
Ming Z.
;
Dong Y.
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浏览/下载:14/0
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提交时间:2013/03/25
It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling
shifting
rotation if eigenvectors can not be chosen appropriately. In order to solve this problem
the image is edged
the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively
correctly and quickly.
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