{"id":1791,"date":"2017-10-13T22:44:31","date_gmt":"2017-10-13T20:44:31","guid":{"rendered":"https:\/\/www.adimec.com\/camera-requirements-for-3d-metrology\/"},"modified":"2018-07-27T16:09:23","modified_gmt":"2018-07-27T14:09:23","slug":"camera-requirements-for-3d-metrology","status":"publish","type":"post","link":"https:\/\/www.adimec.com\/ja\/camera-requirements-for-3d-metrology\/","title":{"rendered":"Camera Requirements for 3D Metrology"},"content":{"rendered":"<div class=\"hs-migrated-cms-post\">\n<p>The increasing trend from 2D measurements to 3D in <a href=\"https:\/\/www.adimec.com\/markets-2\/\" title=\"semiconductor\" target=\"_blank\">semiconductor<\/a> and <a href=\"https:\/\/www.adimec.com\/markets-2\/\" title=\"electronics metrology\" target=\"_blank\">electronics metrology<\/a> and inspection systems results in more stringent requirements for the OEM camera. &nbsp;<\/p>\n<p><!--more--><\/p>\n<p>There are camera parameters to consider in addition to resolution and frame speed for accurate 3D metrology.&nbsp; Here are some other machine vision camera parameters to include when analyzing the fit of a camera within an automation system:<\/p>\n<ul>\n<li>Resolution (horizontal x vertical pixels)<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">Today 4 to 25 Megapixel cameras are common.&nbsp; Higher resolution allows for larger inspection areas and\/or higher accuracy<\/p>\n<ul>\n<li>Pixel size<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">Whereas consumer cameras have pixels that are less than 1 um in size, machine vision cameras typically have pixel sizes ranging from 4 to 10um.&nbsp; Smaller pixels may result in cheaper cameras at the cost of poorer measurement accuracy.<\/p>\n<ul>\n<li>Frame speed<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">System speed is one of the most important selling points for in-line equipment manufacturers; this is directly achieved by increasing frame speed.<\/p>\n<ul>\n<li>Digital interface<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">The choices greatly influence system design as it determines cable length, flexibility, and overall system costs<\/p>\n<ul>\n<li>Functionality and software support<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">This is important during the design phase, but it also influences maintenance costs during the lifetime of the equipment.<\/p>\n<ul>\n<li>Spectral response<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">The image sensor\u2019s spectral response has to match the spectral response of the light source used.&nbsp; A poor match between illuminator wavelength and sensor quantum efficiency (Qe) results in poor measurement accuracy due to too much noise in the image, or will lead to the selection of a more expensive light source.<\/p>\n<ul>\n<li>Read noise<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">This determines the noise floor in dark image areas and influences the accuracy of the measurement<\/p>\n<ul>\n<li>Full well capacity<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">This determines the noise in bright areas of the image and influences the accuracy of the measurement<\/p>\n<ul>\n<li>Photo response linearity<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">Most measurement methods assume a linear response of the pixel to light but this may not be true from raw image sensor output<\/p>\n<ul>\n<li>Image non-uniformities<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">Dark signal non-uniformity (DSNU), photo response non-uniformity (PRNU), striping, shading, and defective pixels, columns and rows all influence measurement accuracy<\/p>\n<ul>\n<li>Modular transfer function (MTF)<\/li>\n<\/ul>\n<p style=\"padding-left: 30px;\">The MTF determines how \u201csharp\u201d the image is and determines the smallest errors that can be detected and the measurement accuracy.&nbsp; Note that the MTF of an image sensor is wavelength-dependent and in general deteriorates at longer wavelengths (such as near-infrared light)<\/p>\n<p>&nbsp;<\/p>\n<p>Not all of these parameters can be optimized at the same time and the most important specifications depend on the application. &nbsp;With the most critical specifications prioritized, unnecessary costs can be avoided. There are several measurement methods commonly used in semiconductor and electronics manufacturing, which provide good examples for this.<\/p>\n<p>Our <a href=\"\/3d-metrology-oem-camera-requirements\/\" title=\"free ePaper\" target=\"_blank\">free ePaper<\/a> discusses critical parameters depending on the specific measurement.&nbsp; A few applications will be described in detail to demonstrate how to determine the most important camera parameters.<\/p>\n<p>&nbsp;<\/p>\n<p>Click below to download our free ePaper on Camera Requirements for 3D Metrology.<\/p>\n<p><a href=\"\/3d-metrology-oem-camera-requirements\/\" target=\"_blank\"><img decoding=\"async\" id=\"img-1412255238126\" src=\"\/\/cdn2.hubspot.net\/hub\/20421\/file-1343205583-jpg\/images\/cta-3d-metrology-camera-requirements_copy.jpg\" border=\"0\" alt=\"3d-metrology-oem-camera\" \/><\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>The increasing trend from 2D measurements to 3D in semiconductor and electronics metrology and inspection syst&hellip;<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1791","post","type-post","status-publish","format-standard","hentry","category-uncategorized","category-1","description-off"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.9 - 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