Title :
Research on Product Optical Image Position Distribution in Machine Vision System Based on Mathematical Statistics
Author_Institution :
Sch. of Art & Commun., Xi´´an Technol. Univ., Xi´´an, China
fDate :
July 31 2012-Aug. 2 2012
Abstract :
Aim to industrial product parameter´s measurement and dependability analysis, the technology of machine vision and mathematical statistics were applied to verify and analyze product optical image central deviating from optical axis position distribution, the center of product image deviating from optical axis would bring great measure error. To reduce those errors, this paper proposes a method of hypothesis testing to analyze the position distribution about center of product optical image deviating from optical axis. According to the optical image calculation processing arithmetic, the performance of optical system and its affect on product´s parameter measurement was studied. The position distribution about the center of product image optical central deviating from optical axis is tested by normal distribution, Raleigh distribution and exponential distribution. The results show that exponential distribution is relatively reasonable.
Keywords :
CAD; computer vision; exponential distribution; normal distribution; product design; production engineering computing; CAD; Raleigh distribution; exponential distribution; industrial design; industrial product parameter dependability analysis; industrial product parameter measurement; machine vision system; mathematical statistics; normal distribution; optical axis; product design; product optical image central analysis; product optical image central verification; product optical image position distribution; Adaptive optics; Exponential distribution; Machine vision; Optical design; Optical imaging; Optical variables measurement; Visualization; CAD; industrial design; machine vision; product design;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location :
GuiLin
Print_ISBN :
978-1-4673-2217-1
DOI :
10.1109/ICDMA.2012.164