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	Design of Greenhouse Control System Based on Edge Computing 会议论文 OAI收割 Xi'an, China, November 25-28, 2021 作者: Han WL(韩文龙); Feng AS(封岸松); Xiao JC(肖金超); Zi SF(资双飞) \| 收藏 \| 浏览/下载：21/0 \| 提交时间：2022/03/07 edge calculation edge controller fuzzy control greenhouse
	beta-CsB9O14: A Triple-Layered Borate with Edge-Sharing BO4 Tetrahedra Exhibiting a Short Cutoff Edge and a Large Birefringence 期刊论文 OAI收割 CHEMISTRY-A EUROPEAN JOURNAL, 2019, 卷号: 25, 期号: 50, 页码: 11614-11619 作者: Han, SJ (Han, Shujuan) [1]; Huang, CM (Huang, Chunmei) [1] , [2]; Tudi, A (Tudi, Abudukadi) [1] , [2]; Hu, SS (Hu, Shuaishuai) [1] , [2]; Yang, ZH (Yang, Zhihua) [1] \| 收藏 \| 浏览/下载：14/0 \| 提交时间：2022/02/21 deep-ultraviolet edge-sharing BO4 large birefringence theoretical calculation triple-layered borate
	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：21/0 \| 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.
	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：60/0 \| 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).
	The removal function of edge effect and amending with dwell time function (EI CONFERENCE) 会议论文 OAI收割 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, April 26, 2010 - April 29, 2010, Dalian, China 作者: Luo X.; Zhang F.; Zhang F.; Wang X.-K.; Zheng L.-G. 收藏 \| 浏览/下载：35/0 \| 提交时间：2013/03/25 Computer Controlled Optical Surfacing (CCOS) is widely used for making optical aspheric mirrors. In the practical fabrication edge effect is an important problem which restricts the fabrication efficiency and accuracy seriously. In this paper the edge effect is solved by working out the edge removal function and compensate with dwell time function. Skin Model is used to describe the pressure distribution when the tool hangs over the work-piece. The calculation model of edge removal function is derived from Skin Model theoretically. A removal function experiment is completed. The difference between the theoretical model and the experiment results is less than 5%. It means that the calculation model is suit for the practical fabrication. Than the dwell time is solved with edge effect compensation by matrix-based algorithm. In the end actual experiment was done to validate the edge effect compensation method. 2010 Copyright SPIE - The International Society for Optical Engineering.
	Real time tracking by LOPF algorithm with mixture model (EI CONFERENCE) 会议论文 OAI收割 MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, November 15, 2007 - November 17, 2007, Wuhan, China Meng B.; Zhu M.; Han G.; Wu Z. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently we first use Sobel algorithm to extract the profile of the object. Then we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.
	A new algorithm of image segmentation for overlapping grain image (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Zhang X.; Zhang X.; Zhang X. 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/03/25 Image segmentation is primary issue in image processing at the same time it is principal problem in low level vision in computer vision field. It is the key technology to process image analysis image comprehend and image depict successfully. Aim at measurement of granularity size of nonmetal grain a new algorithm of image segmentation and parameters calculation for overlapping grain image is studied. The hypostasis of this algorithm is present some new attributes of graph sequence from discrete attribute of graph consequently achieve that pick up the geometrical characteristics from input graph and new graph sequence which in favor of image segmentation is recombined. The conception that image edge denoted with "twin-point" is put forward base on geometrical characters of point image edge is transformed into serial edge and on recombined serial image edge based on direction vector definition of line and some additional restricted conditions the segmentation twin-points are searched with thus image segmentation is accomplished. Serial image edge is transformed into twin-point pattern to realize calculation of area and granularity size of nonmetal grain. The inkling and uncertainty on selection of structure element which base on mathematical morphology are avoided in this algorithm and image segmentation and parameters calculation are realized without changing grain's self statistical characters.