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	Study on optimum line configuration for location model in computer vision 期刊论文 OAI收割 Applied Mathematics and Information Sciences, 2015, 卷号: 9, 期号: 2, 页码: 1029-1035 作者: Qin LJ(秦丽娟); Wang T(王挺); Liu XF( 刘小芳); Yao C(姚辰); Hu YL(胡玉兰) \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2021/03/14 Optimum line configuration Quadrangular frustum pyramid Location model Quantization errors Computer vision
	Analysis of measuring errors for the visible light phase-shifting point diffraction interferometer (EI CONFERENCE) 会议论文 OAI收割 2010 OSA-IEEE-COS Advances in Optoelectronics and Micro/Nano-Optics, AOM 2010, December 3, 2010 - December 6, 2010, Guangzhou, China 作者: Zhang Y. 收藏 \| 浏览/下载：18/0 \| 提交时间：2013/03/25 In order to improve the measuring accuracy of the visible light phase-shifting point diffraction interferometer (PS/PDI) for the extreme ultraviolet lithography (EUVL) aspheric mirrors the main measuring errors will be discussed in this paper. At first the elementary configuration and measuring principle of the visible light phase-shifting point diffraction interferometer are introduced briefly then the different errors which are possible to affect the measuring result are summed up the errors include PZT phase-shifting error detector nonlinearity error detector quantization error wavelength instability error and intensity instability error of the laser source vibration error air refractivity instability error and so on. Through detailed analysis and simulation the magnitude of these errors can be obtained. By analysing the reasons which cause these errors and the relationship between these errors and interferometer configuration parameters some methods are put forward to avoid or restrain these errors accordingly.
	A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Yao Z.-J. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However 3. applying the standard Hough transform equation to every point of the input image edge 4. according to the local threshold 6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes traditional Hough transform can only detect the lines 2. quantizing the parameter space and extracting a group of maximums according to the global threshold eliminating spurious peaks which are caused by the spreading effects and will improve the precision of tracking. cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately 5. fixing on the endpoints of the segments according to the dynamic clustering rule which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image parameter and line-segment spaces