中国开放科研知识云: 检索

On hyperspectral remotely sensed image classification based on MNF and AdaBoosting (EI CONFERENCE) 会议论文
2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012, July 16, 2012 - July 18, 2012, Shanghai, China
Xu Y.; Yu P.; Guo B.; Gao X.; Guo Y.

收藏 | 浏览/下载：16/0 | 提交时间：2013/03/25

As an effective statistical learning tool AdaBoosting has been widely used in the field of pattern recognition. In this paper a new method is proposed to improve the classification performance of hyperspectral images by combining the minimum noise fraction (MNF) and AdaBoosting. Because the hyperspectral imagery has many bands which have strong correlation and high redundancy the hyperspectral data are pre-processed by the minimum noise fraction to reduce the data's dimensionality whilst to remove noise bands simultaneously. Then we use an AdaBoost algorithm to conduct the classification of hyperspectral remotely sensed image. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well. 2012 IEEE.

An improved hyperspectral classification algorithm based on back-propagation neural networks (EI CONFERENCE) 会议论文
2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China
Mao W.; Yu P.; Guo B.; Xu Y.; Chen H.

收藏 | 浏览/下载：19/0 | 提交时间：2013/03/25

In this paper a new method is proposed to improve the classification performance of hyperspectral images by combining the principal component analysis (PCA) genetic algorithm (GA) and artificial neural networks (ANNs). First some characteristics of the hyperspectral remotely sensed data such as high correlation high redundancy etc. are investigated. Based on the above analysis we propose to use the principal component analysis to capture the main information existing in the hyperspectral images and reduce its dimensionality consequently. Next we use neural networks to classify the reduced hyperspectral data. Since the back-propagation neural network we used is easy to suffer from the local minimum problem we adopt a genetic algorithm to optimize the BP network's weights and the threshold. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well. 2012 IEEE.

Image registration based on Mexican-hat wavelets and pseudo-Zernike moments (EI CONFERENCE) 会议论文
2012 World Automation Congress, WAC 2012, June 24, 2012 - June 28, 2012, Puerto Vallarta, Mexico
Ding N.; Liu Y.

收藏 | 浏览/下载：30/0 | 提交时间：2013/03/25

Image registration is a key technique in pattern recognition and image processing and it is widely used in many application areas such as computer vision remote sensing image fusion and object tracking. A method for image registration combining Mexican-hat wavelets and pseudo-Zernike moments is proposed. Firstly feature points are extracted using scale-interaction Mexican-hat wavelets in the reference image and sensed image respectively. Then pseudo-Zernike moments are used to match them and classical RANSAC used to eliminate the wrong matches. And then the well match points are used to estimate the best affine transform parameters by least squares minimization. At last the sensed image is transformed and resampled to accomplish the image registration. The experiments indicate that the proposed algorithm extracts feature points and matches them exactly and eliminates wrong matched points effectively and achieves nice registration results. 2012 TSI Press.

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.

收藏 | 浏览/下载：31/0 | 提交时间：2013/03/25

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.

收藏 | 浏览/下载：29/0 | 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.

收藏 | 浏览/下载：50/0 | 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).

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.

收藏 | 浏览/下载：16/0 | 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.

Research of computer control system for laser warning HWIL simulation (EI CONFERENCE) 会议论文
2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China
Zhang P.-I.; Wang J.-J.

收藏 | 浏览/下载：14/0 | 提交时间：2013/03/25

A computer control system is proposed which is based on hardware-in-loop(HWIL) simulation test system. As an important sub-system in simulation test system the reality is the focus of the simulation system. The construction of the computer control system for laser warning based on HLA Distributed Simulation. By combining the outer clock and time stamp for data frame data interaction is triggered by outer clock the simulation process is propelled. The simulation terminal devices are also controlled by the outer clock. The simulation test is done by the above method. The result shows that the data interaction time less than lms and it meet the need of reality for control so it is effective. 2010 IEEE.

Adaptive deformation estimation of moving target by weight image analysis (EI CONFERENCE) 会议论文
2010 2nd International Conference on Future Computer and Communication, ICFCC 2010, May 21, 2010 - May 24, 2010, Wuhan, China
Bai X.-G.; Dai M.

收藏 | 浏览/下载：21/0 | 提交时间：2013/03/25

An algorithm based on weight image analysis is proposed for adaptive deformation estimation of moving target in mean-shift tracking method. At the first we get the weight image from the target candidate region. Then we analyze the differences between the object and background. According to that the area estimation of the target can be converted into the image segmentation task. To realize the adaptive segmentation and estimation we define the threshold as the maximum variance between object and background. Combining the estimated area and covariance matrix we can estimate the width height and orientation of the object. The experimental results on three representative video sequences validate its robustness to the deformable estimation of the targets. 2010 IEEE.

Scene matching based on directional keylines and polar transform (EI CONFERENCE) 会议论文
2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China
Zhang Y.; Qu H.; Wang Y.

收藏 | 浏览/下载：19/0 | 提交时间：2013/03/25

Scene matching under complex background is a priority and difficulty in the field of computer vision it has the characteristics of rotation and scaling invariance commonly used in matching real-time collected images and photos for navigation. Scene matching techniques are faced with complex natural scenes anti-light and anti-slight-distortion the image distortion exist applicable for complex scene matching. The project has a new idea: combining the keylines with the vectors description based on polar image translation such as light and utilize the rotation-scale-invariance vectors to describe the extracted keylines change of gray levels this method includes three steps: keylines extraction perspective description and matching. Preliminary experiments show that this keylines-based scene matching algorithm is applicable for image matching under complex background. 2010 IEEE. scaling and other differences which cause matching difficult. This paper aims to find a scene matching algorithm

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