中国科学院机构知识库网格系统: 检索

The roles of edge-based and surface-based information in the dynamic neural representation of objects 期刊论文 OAI收割
NEUROIMAGE, 2023, 卷号: 283, 页码: 11
作者: Yao, Liansheng; Fu, Qiufang; Liu, Chang Hong

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收藏 | 浏览/下载：17/0 | 提交时间：2023/12/18

Neural representation of objects Edge-based information Surface-based information EEG MVPA

Research on attribute-based encryption access control technology in edge computing environment 会议论文 OAI收割
Beijing, China, October 22-24, 2021
作者: Jiang YH(蒋一恒); Zhang Chen; Zhang BW(张博文)(2.3); Yuan DC(袁德成); Wang C(王晨)

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收藏 | 浏览/下载：27/0 | 提交时间：2022/04/23

access control attribute-based encryption edge computing edge nodes information security

The Role of Edge-based and Surface-based Information in Incidental Category Learning: Evidence from Behavior and Event-related Potentials 会议论文 OAI收割
曲阜, 2017.7.1
作者: Xiaoyan Zhou; Qiufang Fu

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收藏 | 浏览/下载：24/0 | 提交时间：2017/12/28

edge-based information surface-based information categorization

Corner detection using Gabor filters 期刊论文 OAI收割
iet image processing, 2014, 卷号: 8, 期号: 11, 页码: 639-646
作者: Zhang, Wei-Chuan; Wang, Fu-Ping; Zhu, Lei; Zhou, Zuo-Feng

收藏 | 浏览/下载：51/0 | 提交时间：2015/03/19

edge detection Gabor filters grey systems affine transforms Gabor filter contour-based corner detection magnitude response edge contour shape analysis local curvature maxima points planar curve corresponding grey-variation information Canny edge detector normalised magnitude response magnitude response threshold angle threshold detection accuracy localisation accuracy afflne transform noise-robustness

The shape edge measure of automobile airbag based on image processing (EI CONFERENCE) 会议论文 OAI收割
2012 IEEE 5th International Conference on Advanced Computational Intelligence, ICACI 2012, October 18, 2012 - October 20, 2012, Nanjing, China
作者: Li Y.; Wang Z.; Wang Z.; Li Y.; Li Y.

收藏 | 浏览/下载：33/0 | 提交时间：2013/03/25

At present micrometer is used for measure the shape edge of automobile airbag. There are some shortcomings in this method. The number of test points is limited. Test data is not comprehensive. Detection speed is slow and a fixture can only test a kind of airbag. The method of airbag shape edge detection based on image processing is researched in this paper. The image of airbag is collected by CCD and then it is sent to the computer to be processed and segmented. The edge of image is extracted through Canny edge detection algorithm in order to acquire shape edge of airbag in this paper and the image similarity degree are calculated to provide the information of matching in the template matching process. Finally the comprehensive test shape edge of airbag is realized. The experimental results show that the detection method is effective feasible intuitive and clear. 2012 IEEE.

Image mosaic technique based on the information of edge (EI CONFERENCE) 会议论文 OAI收割
2012 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012, July 31, 2012 - August 2, 2012, Guilin, Guangxi, China
作者: Wang Y.-Q.

收藏 | 浏览/下载：34/0 | 提交时间：2013/03/25

Image mosaic is an important branch in the field of image processing. This paper designs and realizes an image mosaic technique based on the information of edge. The technology is suitable for engineering application. First of all two images of the adjoining frames are processed by convolution operation get the edge images. And then we cut edge image into pieces and compute their spatial frequency. According to the value of the spatial frequency select reasonable registration model group. We compute correlation strength and the value of movement offset which are the model group and the current frame edge image. We can complete image mosaic by them. We use video sequence which of the resolution is 1024 * 768 do the experiment. The results show that the method has good effect and strong adaptability. Algorithm is high efficiency which running time is 24 ms. It is suitable for real-time processing requirements of the application. This method is an effective mosaic technique which is suitable for engineering application. 2012 IEEE.

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.

收藏 | 浏览/下载：75/0 | 提交时间：2013/03/25

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).

Multi-scale edge extraction based stereo matching algorithm (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010, December 11, 2010 - December 12, 2010, Chongqing, China
作者: Li L.

收藏 | 浏览/下载：14/0 | 提交时间：2013/03/25

In the field of robot vision edge feature based stereo matching algorithm can reconstruct the targets with clear contours which needs accurate and continuous target edges been extracted. In the paper the smoothing filter operator was designed based on the discrete criteria of edge extraction and its correspondence optimal linear filter. Edge extraction was carried out incorporated the nonmaximum suppression and two thresholds techniques. The discrete criteria based multi-scale edge extraction method was studied with full use of the multi-scale character of the edge information. The detected multi-scale edges were synthesized to obtain the accurate and continuous single pixel wide edge. Then an edge feature based stereo matching algorithm was proposed to obtain 3D information of target. The experimental results demonstrate that the method can effectively suppress disturbance in outdoor environment and reconstruct target contour clearly. (2011) Trans Tech Publications.

Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 OAI收割
6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China
Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge we extract the river regions which the bridges are included in. Firstly we segment the optical image to get the coarse water bodies using iterative threshold eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.