中国科学院机构知识库网格系统: 检索

Gray BP neural network based prediction of rice protein interaction network. 期刊论文 OAI收割
Cluster Computing, 2018
作者: Wang X(王雪)

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Gray value BP neural network Rice protein interaction Prediction

Moving target detection and classification using spiking neural networks (EI CONFERENCE) 会议论文 OAI收割
2nd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2011, October 23, 2011 - October 25, 2011, Xi'an, China
作者: Sun H.; Wang Z.; Wang Z.; Wang P.; Sun H.

收藏 | 浏览/下载：40/0 | 提交时间：2013/03/25

We proposed a spiking neural network (SNN) to detect moving target in video streams and classify them into real categorization in this paper. The proposed SNN uses spike trains to encoding information such as the gray value of pixels or feature parameters of the target detects moving target by simulating the visual cortex for motion detection in biological system with axonal delays and classify them into different categorizations according to their distance to categorization's centers found by Hebb learning rule. The experimental results show that the proposed SNN is promising in intelligence computation and applicable in general visual surveillance system. 2012 Springer-Verlag.

Space camera dynamic image quality measurement and evaluation (EI CONFERENCE) 会议论文 OAI收割
3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011, January 6, 2011 - January 7, 2011, Shanghai, China
作者: Zhang X.; Zhang X.; Zhang X.

收藏 | 浏览/下载：20/0 | 提交时间：2013/03/25

By using analysis of the infinity image of the space camera we intend to obtain the curve of the dynamic modulation transfer function. We extract the pixel gray values at the image edge which distribute as a knife-edge function and make differential calculation and Fourier transformation of it and then we can obtain the dynamic MTF curve of the optical system. The value of the curve at the Nyquist frequency is the most important parameter that reflects the image quality. We add push-scanning imaging and environmental effects to the static MTF of space camera and compare the MTF value with the dynamic MTF at Nyquist frequency. The comparison result can help us verify the accuracy of the calculating results and the feasibility of our method. (2011) Trans Tech Publications.

Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Wu Z.-G.; Wang M.-J.; Han G.-L.

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Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.

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：57/0 | 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).

An adaptive edge detection method based on Canny operator (EI CONFERENCE) 会议论文 OAI收割
2011 International Conference on Civil Engineering and Building Materials, CEBM 2011, July 29, 2011 - July 31, 2011, Kunming, China
作者: Chen Y.

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This paper proposes an adaptive Canny operator edge detection algorithm. The proposed method can automatically set the threshold value according to the different image gray-scale gradient histogram adaptively and improve the performance in the detail edge detection and good localization. Experiments show that this method produces better edge detection results performance than the Otsu method. Besides our method Roberts operator Prewitt operator Sobel operator Log operator and Canny operator based on Otsu algorithm are also tested for comparisons. (2011) Trans Tech Publications Switzerland.

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：109/0 | 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).

The corner detector of teeth image based on the improved SUSAN algorithm (EI CONFERENCE) 会议论文 OAI收割
3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010, October 16, 2010 - October 18, 2010, Yantai, China
作者: Yang L.; Yang L.; Wang X.; Wang X.; Wang X.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

In order to detect the corners of the teeth image secondly last we detected the corners of the image through the improved SUSAN corner detector algorithm. Through lots of experiments and comparing with other corner detector methods which were acquired by oral cavity endoscope we segmented the image by the threshold based on the gray value of the image this method can detect the corners of the teeth image effectively in this paper which can offer some available parameters for the 3D reconstruction of the teeth. 2010 IEEE. we used the improved SUSAN corner detector algorithm. In this method firstly we removed the noise of the image by the morphology open operation and median filtering

The research of corner detector of teeth image based on the curvature scale space corner algorithm (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
作者:

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

In order to detect the corners of the teeth image secondly thirdly last this method can detects the corners of the teeth image effectively which were acquired by oral cavity endoscope we segmented the image by the threshold based on the gray value of the image we detected the edge of the teeth image by the Canny edge detector we detected the corners by the adaptive threshold curvature scale corner detector. Through lots of experiments and we compare this method to other corner detector methods which offers some available parameters for the 3D reconstruction of the teeth. 2010 IEEE. in this paper we used the CSS algorithm. In this method firstly we removed the noise of the image by the morphology open operation and median filtering

An adaptive enhancement means adapt to CR medicine image (EI CONFERENCE) 会议论文 OAI收割
International Conference on Image Processing and Pattern Recognition in Industrial Engineering, August 7, 2010 - August 8, 2010, Xi'an, China
Zhang M.-H.; Zhang Y.-Y.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

It puts forward CR medicine image adaptive enhancement arithmetic based on the ratio of image variance to noise variance which can adjust factor K bases on CR image gray characteristic and enhance image detail and improve image diagnosis value. Experiment results demonstrate that the algorithm enhances CR image detail and the value of DV/BV was higher than the other algorithms moreover CR image enhanced has good visual effect the method is fit for edge detail enhancement of CR medicine radiation image. 2010 SPIE.