机构

• 长春光学精密机械与物... [2]

采集方式

• OAI收割 [2]

内容类型

• 会议论文 [2]

发表日期

• 2011 [1]
• 2007 [1]

学科主题

筛选

浏览/检索结果: 共2条，第1-2条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 The design of chisel-edge ruling tool for diffraction gratings (EI CONFERENCE) 会议论文  OAI收割 2011 International Conference on Mechatronic Science, Electric Engineering and Computer, MEC 2011, August 19, 2011 - August 22, 2011, Jilin, China 作者:  Zhang F.;  Zhang F. 收藏  |  浏览/下载：26/0  |  提交时间：2013/03/25 The process of parameters design on chisel-edge ruling tool of diffraction grating  which is inefficient and highly costive  needs plenty ruling experience came from a series of ruling test to optimize and design it. In order to reduce the choosing range of experiential design parameters on chisel-edge grating ruling tool  to improve efficiency  and to reduce costs  this paper summarize the experimental results of several gratings ruling process for the experiential design on parameters of chisel-edge ruling tool. Provide the specific parameters choosing range as follows: that the blaze angle and directional angle difference in less than 3  the bottom angle and apex angle difference in less than 5. Apex angle larger than the groove bottom angle in conventional grating  while apex angle smaller than the bottom angle in echelle grating  and the directional angle smaller than blaze angle in both condition. 2011 IEEE.   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.