{"id":96,"date":"2015-07-24T18:38:00","date_gmt":"2015-07-24T18:38:00","guid":{"rendered":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2015\/07\/24\/imaging-basics-calculating-resolution-for-machine-vision\/"},"modified":"2023-04-21T13:22:35","modified_gmt":"2023-04-21T17:22:35","slug":"imaging-basics-calculating-resolution","status":"publish","type":"post","link":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2015\/07\/imaging-basics-calculating-resolution.html","title":{"rendered":"Imaging Basics:  How to Calculate Resolution for Machine Vision"},"content":{"rendered":"<p><span style=\"font-size: small;\">\u00a0<\/span><\/p>\n<div style=\"clear: left; float: left; line-height: normal; margin-bottom: 1em; margin-right: 1em;\"><span style=\"font-family: Arial, Helvetica,sans-serif;\"><span style=\"font-size: small;\">\u00a0<\/span><\/span><\/div>\n<p><a style=\"clear: left; float: left; margin-bottom: 1em; margin-right: 1em;\" 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Shading Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"72\" Name=\"Colorful List Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"73\" Name=\"Colorful Grid Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"60\" Name=\"Light Shading Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"61\" Name=\"Light List Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"62\" Name=\"Light Grid Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"63\" Name=\"Medium Shading 1 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"64\" Name=\"Medium Shading 2 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"65\" Name=\"Medium List 1 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"66\" Name=\"Medium List 2 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"67\" Name=\"Medium Grid 1 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"68\" Name=\"Medium Grid 2 Accent 6\"\/>  <w:LsdException Locked=\"false\" 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<w:LsdException Locked=\"false\" Priority=\"46\" Name=\"Grid Table 1 Light Accent 4\"\/>  <w:LsdException Locked=\"false\" Priority=\"47\" Name=\"Grid Table 2 Accent 4\"\/>  <w:LsdException Locked=\"false\" Priority=\"48\" Name=\"Grid Table 3 Accent 4\"\/>  <w:LsdException Locked=\"false\" Priority=\"49\" Name=\"Grid Table 4 Accent 4\"\/>  <w:LsdException Locked=\"false\" Priority=\"50\" Name=\"Grid Table 5 Dark Accent 4\"\/>  <w:LsdException Locked=\"false\" Priority=\"51\" Name=\"Grid Table 6 Colorful Accent 4\"\/>  <w:LsdException Locked=\"false\" Priority=\"52\" Name=\"Grid Table 7 Colorful Accent 4\"\/>  <w:LsdException Locked=\"false\" Priority=\"46\" Name=\"Grid Table 1 Light Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"47\" Name=\"Grid Table 2 Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"48\" Name=\"Grid Table 3 Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"49\" Name=\"Grid Table 4 Accent 5\"\/>  <w:LsdException Locked=\"false\" 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Locked=\"false\" Priority=\"47\" Name=\"List Table 2 Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"48\" Name=\"List Table 3 Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"49\" Name=\"List Table 4 Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"50\" Name=\"List Table 5 Dark Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"51\" Name=\"List Table 6 Colorful Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"52\" Name=\"List Table 7 Colorful Accent 5\"\/>  <w:LsdException Locked=\"false\" Priority=\"46\" Name=\"List Table 1 Light Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"47\" Name=\"List Table 2 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"48\" Name=\"List Table 3 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"49\" Name=\"List Table 4 Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"50\" Name=\"List Table 5 Dark Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"51\" Name=\"List Table 6 Colorful Accent 6\"\/>  <w:LsdException Locked=\"false\" Priority=\"52\" Name=\"List Table 7 Colorful Accent 6\"\/> <\/w:LatentStyles><\/xml><![endif]--><!-- [if gte mso 10]><![endif]--><\/p>\n<div style=\"clear: left; float: left; line-height: normal; margin-bottom: 1em; margin-right: 1em;\"><span style=\"font-family: Arial,Helvetica,sans-serif;\"><span style=\"font-size: small;\">\u00a0<\/span><\/span><\/div>\n<div style=\"line-height: normal; margin-bottom: 0.0001pt; text-align: left;\"><span style=\"font-size: small;\"><span style=\"font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman';\"><span style=\"font-family: Arial, Helvetica, sans-serif;\">Camera image resolution is defined by the number of pixels in a given CCD or CMOS sensor array.<span style=\"mso-spacerun: yes;\">\u00a0 <\/span>This will be identified in a camera data sheet and shown as the number of pixels in the X and Y axis (i.e 1600 x 1200 pixels).<span style=\"mso-spacerun: yes;\">\u00a0 <\/span><\/span><\/span><\/span><\/div>\n<div style=\"line-height: normal; margin-bottom: 0in;\"><\/div>\n<div style=\"line-height: normal; margin-bottom: 0in;\">\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><span style=\"font-family: Arial, sans-serif;\">The application will determine how many pixels are required in order to identify a desired feature accurately.\u00a0\u00a0This also assumes you have a perfect lens that is not limiting resolving the pixel (<a href=\"https:\/\/www.1stvision.com\/machine-vision-solutions\/2015\/06\/demystifying-lens-performance.html\" target=\"_blank\" rel=\"noopener\"><b>see Demystifying lens specifications<\/b><\/a>).\u00a0\u00a0In general more pixels is better and will provide better accuracy and repeatability.\u00a0\u00a0<\/span><\/div>\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><\/div>\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><span style=\"font-family: Arial, sans-serif; font-size: 13.5pt;\">\u00a0<\/span><\/div>\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><span style=\"font-family: Arial, sans-serif;\">\u00a0If for example you have a dark hole on a white background filling your field of view (FOV) by 90%, you will have many pixels across the feature.\u00a0\u00a0On the contrary, if we have a small pin hole that is within the same field of view, we may not have enough pixels across the hole to identify the feature.\u00a0\u00a0In order to find an edge you need at a minimum of 2 pixels given excellent contrast.\u00a0\u00a0In order to be robust you ideally will want 3-4 pixels across a edge or feature.\u00a0\u00a0<\/span><\/div>\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><\/div>\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><span style=\"font-family: Arial, sans-serif;\">This leads us to identifying the resolution required given the size of a feature.\u00a0 We will do this with an example and provide the needed formulas on how to calculate the resolution.<\/span><\/div>\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><\/div>\n<div style=\"margin-bottom: .0001pt; margin: 0in;\"><b><span style=\"font-family: Arial, sans-serif;\">Example:<\/span><\/b><span style=\"font-family: Arial, sans-serif;\">\u00a0 The vision inspection is to locate a pin hole which is 0.25mm in diameter on a part which is 20mm square.\u00a0 In order to compensate for any misplacement of the part, we will set our FOV to 40mm x 30mm.\u00a0 We would also like to have a minimum of 4 pixels across the 0.25mm feature. \u00a0<\/span><\/div>\n<\/div>\n<div style=\"line-height: normal; margin-bottom: 0in;\"><span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\"><u><b>We can calculate the resolution required as follows: <\/b><\/u><\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">Where:<\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">Rs is the spatial resolution (maybe either X or Y)<\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif; font-size: small;\">FOV is the field of view dimensions (mm)\u00a0 in either X or Y<\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif; font-size: small;\">Ri is the image sensor resolution; number of pixels in a row (X dimension) or column (Y dimension)<\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif; font-size: small;\">Rf is the feature resolution (smallest feature that must be reliably resolved) in physical units (mm)<\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif; font-size: small;\">Fp is the number of desired pixels that will span a feature of minimum size. <\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">For this case we know:\u00a0 <\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">FOV(x) =\u00a0 40mm<\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif; font-size: small;\">Rf = 0.25mm<\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif; font-size: small;\">Fp = 4 pixels <\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">Calculating the spatial resolution (Rs) needed: <\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif; font-size: small;\">Rs = Rf \/ Fp = 0.25mm \/ 4 pixels = 0.0625mm pixel<\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">From the spatial resolution (Rs) and the field of view (FOV), we can determine the image resolution (Ri) required (we have only calculated for the x-axis) using this calculation: <\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">Ri = FOV \/ Rs = 40mm \/ 0.0625 mm\/pixel = 640 pixels<\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">We have now determined that we need a minimum resolution of 640 pixels in the x-axis to provide 4 pixels across our feature that is 0.25mm in diameter. The camera resolution can now be selected!\u00a0 In today&#8217;s world, we could select a VGA (640 x 480) camera for the application.\u00a0 As a note, the number of pixels required depends on many aspects of lighting, optics and algorithms used for processing.\u00a0 This calculation method assumes optimum conditions. \u00a0 \u00a0\u00a0 <\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">If you do not like math, you can download our resolution calculator here and just enter the data.\u00a0 This makes it easy to test various iterations.\u00a0 Download the calculator <b><a href=\"https:\/\/www.1stvision.com\/disclaimer-calculate-your-camera-resolution\" target=\"_blank\" rel=\"noopener\">HERE.<\/a>\u00a0 <\/b><\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">If you visit our <a href=\"https:\/\/www.1stvision.com\/cameras\/industrialCameras\" target=\"_blank\" rel=\"noopener\"><b>camera page<\/b><\/a>, you can sort by resolution in X and Y resolutions to quickly ID cameras that meet your resolution needs.\u00a0 <\/span><\/span><br \/>\n<span style=\"font-family: Arial, Helvetica, sans-serif;\"><span style=\"font-size: small;\"><br \/>\n<\/span><span style=\"font-size: small;\">For all your imaging needs, you can visit <b><a href=\"http:\/\/www.1stvision.com\/\" target=\"_blank\" rel=\"noopener\">www.1stvision<\/a> <\/b>or <b><a href=\"http:\/\/1stvision.com\/contact.html\" target=\"_blank\" rel=\"noopener\">contact us!<\/a>\u00a0<\/b>to discuss your application in further detail or receive a quote on a desired camera.\u00a0 We can also help identify which sensor is best based on the imaging conditions. \u00a0 <\/span><\/span><\/div>\n<div style=\"line-height: normal; margin-bottom: 0in;\"><\/div>\n<div style=\"line-height: normal; margin-bottom: 0in;\"><\/div>\n<div style=\"line-height: normal; margin-bottom: 0in;\"><\/div>\n<div style=\"text-align: center;\"><a href=\"https:\/\/www.youtube.com\/user\/1stVisionInc\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"http:\/\/4.bp.blogspot.com\/-tiumm-k4HNw\/VbEO7RYPBII\/AAAAAAAAOck\/IWcJqYQjRcY\/s320\/youtube24.png\" alt=\" \" border=\"0\" \/><\/a>\u00a0\u00a0\u00a0 <a href=\"https:\/\/www.facebook.com\/pages\/1st-Vision\/944658058935262?fref=ts\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"http:\/\/4.bp.blogspot.com\/-EY6c1JsMg_I\/VbEO6_bRtHI\/AAAAAAAAOcU\/KeCM9m6ynt8\/s320\/facebook24.png\" alt=\"https:\/\/www.facebook.com\/pages\/1st-Vision\/944658058935262?fref=ts\" border=\"0\" \/><\/a>\u00a0\u00a0\u00a0 <a href=\"https:\/\/plus.google.com\/+1stvision_imaging\/posts\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"http:\/\/3.bp.blogspot.com\/-us8y5ck2pJs\/VbEO61rPmBI\/AAAAAAAAOcY\/fq4c83yH9sM\/s320\/google-plus1%2B24.png\" alt=\" \" border=\"0\" \/><\/a>\u00a0\u00a0\u00a0 <a href=\"https:\/\/www.linkedin.com\/company\/1stvision-inc-\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"http:\/\/3.bp.blogspot.com\/-IeK73AsufBY\/VbEO7CZwehI\/AAAAAAAAOc8\/_CVnJ8Yl878\/s320\/linkedin1%2B24.png\" alt=\" \" border=\"0\" \/><\/a>\u00a0\u00a0\u00a0 <a href=\"https:\/\/twitter.com\/1stVision_\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"http:\/\/3.bp.blogspot.com\/-5umPEkuIopM\/VbEO7dKtnVI\/AAAAAAAAOcs\/kTLxJud2xrM\/s320\/twitter-24.png\" alt=\" \" border=\"0\" \/><\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>\u00a0 \u00a0 \u00a0 \u00a0 Camera image resolution is defined by the number of pixels in a given CCD or CMOS sensor array.\u00a0 This will be identified in a camera data sheet and shown as the number of pixels in the X and Y axis (i.e 1600 x 1200 pixels).\u00a0 The application will determine how many &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.1stvision.com\/machine-vision-solutions\/2015\/07\/imaging-basics-calculating-resolution.html\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Imaging Basics:  How to Calculate Resolution for Machine Vision&#8221;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[51,61],"tags":[],"class_list":["post-96","post","type-post","status-publish","format-standard","hentry","category-lenses","category-tutorial"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Imaging Basics: How to Calculate Resolution for Machine Vision<\/title>\n<meta name=\"description\" content=\"Camera image resolution is defined by the number of pixels in a given CCD or CMOS sensor array. 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