中国科学院机构知识库网格系统: 检索

Geometric moment invariants to spatial transform and N-fold symmetric blur 期刊论文 OAI收割
PATTERN RECOGNITION, 2021, 卷号: 115, 页码: 14
作者: Mo, Hanlin; Hao, Hongxiang; Li, Hua

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收藏 | 浏览/下载：25/0 | 提交时间：2021/12/01

Blurred image Blur invariants Moment invariants Spatial transform N-fold symmetry Object recognition Template matching

Star Identification Algorithm Based on Image Normalization and Zernike Moments 期刊论文 OAI收割
IEEE Access, 2020, 卷号: 8, 页码: 29228-29237
作者: Liang, Xiaobo; Ma, Wenli; Zhou, Jin; Kong, Sijie

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收藏 | 浏览/下载：19/0 | 提交时间：2021/05/11

Image normalization star identification Zernike moment

Image Dynamics-Based Visual Servoing for Quadrotors Tracking a Target With a Nonlinear Trajectory Observer 期刊论文 OAI收割
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 卷号: 50, 期号: 1, 页码: 376-384
作者:

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收藏 | 浏览/下载：39/0 | 提交时间：2020/03/30

Target tracking Trajectory Visual servoing Transmission line matrix methods Cameras Visualization Vehicle dynamics Hovering and tracking image moment quadrotor trajectory observer visual servoing

Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment 期刊论文 OAI收割
INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2019, 卷号: 17, 期号: 2, 页码: 16
作者: Lu, Yanfeng; Jia, Lihao; Qiao, Hong; Li, Yi; Qi, Zongshuai

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收藏 | 浏览/下载：83/0 | 提交时间：2019/04/23

Image recognition classification BIM oriented Gaussian-Hermite moment Gabor features patch selection

Multi-source Remote Sensing Image Registration Based on Contourlet Transform and Multiple Feature Fusion 期刊论文 OAI收割
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 575-588
作者: Huan Liu; Gen-Fu Xiao; Yun-Lan Tan; Chun-Juan Ouyang

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收藏 | 浏览/下载：7/0 | 提交时间：2021/02/22

Feature fusion multi-scale circle Gaussian combined invariant moment multi-direction gray level co-occurrence matrix multi-source remote sensing image registration contourlet transform.

Zernike-Moment-Based Image Super Resolution 期刊论文 OAI收割
ieee transactions on image processing, 2011, 卷号: 20, 期号: 10, 页码: 2738-2747
作者: Gao, Xinbo; Wang, Qian; Li, Xuelong; Tao, Dacheng; Zhang, Kaibing

收藏 | 浏览/下载：17/0 | 提交时间：2011/12/27

Fuzzy motion estimation image super resolution (SR) Zernike moment

装配机器人系统的工件定位和抓取装配研究 学位论文 OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2011
作者: 赵广涛

收藏 | 浏览/下载：211/0 | 提交时间：2015/09/02

装配机器人目标检测三维工件定位图像矩抓取点提取 Assembly robot Target recognition Work-piece location Image moment Extraction of the grasp point

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：77/0 | 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 study of mapping relation of aeroplane complex motion and image movement and compensation technique (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer Application and System Modeling, ICCASM 2010, October 22, 2010 - October 24, 2010, Shanxi, Taiyuan, China
Wei Z.; Wang Y.-Y.; Xue W.-Q.; Dai M.

收藏 | 浏览/下载：23/0 | 提交时间：2013/03/25

In order to solve the problem of image blurring due to the image motion which results from the aircraft's motion attitude changes and the relative motion of the camera and aircraft firstly we install linear displacement transducer on the four shock absorbers. By analyzing the displacement values the geometrical relationship between the camera and the aircraft is acquired then relative motion amount between the object and the aircraft is obtained according to the motion and attitude changes. After that making use of geometrical relationship we can calculate the displacement variation of pixels within the camera exposure time. Thereafter taking consider variable motion and non-linear motion as uniform motion in a straight line at the moment of imaging then the model of the blurring image can be established according to the displacement variation of pixels within the camera exposure time and fuzzy point spread function in the two-dimensional movement is built. By using Wiener filtering method with the optimal window the image blurring is eliminated in aerial imaging system. Practice proved that this method can effectively eliminate the image blurring in the aerial imaging system. 2010 IEEE.

Autofocusing technique based on image processing for remote-sensing camera (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing, September 9, 2007 - September 12, 2007, Beijing, China
作者: Wang X.; Xu S.-Y.; Wang X.; Wang X.

收藏 | 浏览/下载：22/0 | 提交时间：2013/03/25

The key to the auto-focusing technique based on image processing is the selection of focus measure reflecting image definition. Usually the measures derived are on the premise of the images acquired with the same scene. As for the remote-sensing camera working in linear CCD push-broom imaging mode the premise doesn't exist because the scenes shot are different at any moment which brings about difficulties to the selection of the focus measure. To evaluate the image definition the focus measure based on blur estimation for rough adjustment is proposed to estimate the focused position by only two different lens positions which greatly saves the auto-focusing time. Another evaluation function based on edge sharpness is developed to find best imaging position in the narrow range. Simulations show that the combination of the two measures has the advantages of rapid reaction and high accuracy.