{"id":1791,"date":"2021-04-09T11:25:08","date_gmt":"2021-04-09T15:25:08","guid":{"rendered":"https:\/\/www.1stvision.com\/machine-vision-solutions\/?p=1791"},"modified":"2021-04-09T12:39:37","modified_gmt":"2021-04-09T16:39:37","slug":"keys-to-choosing-the-best-image-sensor","status":"publish","type":"post","link":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html","title":{"rendered":"Keys to Choosing the Best Image Sensor"},"content":{"rendered":"\n

Image sensors are the key component of any camera and vision system.  This blog summarizes the key concepts of a tech brief addressing concepts essential to sensor performance relative to imaging applications. For a comprehensive analysis of the parameters, you may read the full tech brief<\/strong><\/a>. <\/p>\n\n\n\n

\"Download<\/a><\/figure><\/div>\n\n\n\n

While there are many aspects to consider, here we outline 6 key parameters:<\/p>

  1. Physical parameters<\/strong>

    Resolution<\/strong>: The amount of information per frame (image) is the product of horizontal pixel count x by vertical pixel count y.\u00a0 While consumer cameras boast of resolution like car manufacturers tout horsepower, in machine vision one just needs enough resolution to solve the problem – but not more.\u00a0 Too much resolution leads to more sensor than you need, more bandwidth than you need, and more cost than you need.\u00a0 Takeaway: Match sensor resolution to optical resolution relative to the object(s) you must image.Aspect ratio<\/strong>: Whether 1:1, 3:2, or some other ratio, the optimal arrangement should correspond to the layout of your target\u2019s field of view, so as not to buy more resolution than is needed for your application. \"\"Frame rate<\/strong>: If your target is moving quickly, you\u2019ll need enough images per second to \u201cfreeze\u201d the motion and to keep up with the physical space you are imaging.\u00a0 But as with resolution, one needs just enough speed to solve the problem, and no more, or you would over specify for a faster computer, cabling, etc.Optical format<\/strong>: One could write a thesis on this topic, but the key takeaway is to match the lens\u2019 projection of focused light onto the sensor\u2019s array of pixels, to cover the sensor (and make use of its resolution).\u00a0 Sensor sizes and lens sizes often have legacy names left over from TV standards now decades old, so we\u2019ll skip the details in this blog but invite the reader to read the linked tech brief or speak with a sales engineer, to insure the best fit.<\/p> <\/li>

  2. Quantum Efficiency and Dynamic Range:<\/strong>

    Quantum Efficiency (QE)<\/strong>: Sensors vary in their efficiency at converting photons to electrons, by sensor quality and at varying wavelengths of light, so some sensors are better for certain applications than others. \"Typical Dynamic Range (DR):<\/strong> Factors such as Full Well Capacity and Read Noise determine DR, which is the ratio of maximum signal to the minimum.\u00a0 The greater the DR, the better the sensor can capture the range of bright to dark gradations from the application scene.<\/p> <\/li>

  3. Optical parameters<\/strong>

    While some seemingly-color applications can in fact be solved more easily and cost-effectively with monochrome, in either case each silicon-based pixel converts light (photons) into charge (electrons).\u00a0 Each pixel well has a maximum volume of charge it can handle before saturating.\u00a0 After each exposure, the degree of charge in a given pixel correlates to the amount of light that impinged on that pixel.<\/p> <\/li>

  4. Rolling vs. Global shutter<\/strong>

    Most current sensors support global shutter, where all pixel rows are exposed at once, eliminating motion-induced blur.\u00a0 But the on-sensor electronics to achieve global shutter have certain costs associated, so for some applications it can still make sense to use rolling shutter sensors.<\/p> <\/li>

  5. Pixel Size<\/strong>

    Just as a wide-mouth bucket will catch more raindrops than a coffee cup, a larger physical pixel will admit more photons than a small one.\u00a0 Generally speaking, large pixels are preferred.\u00a0 But that requires the expense of more silicon to support the resolution for a desired x by y array.\u00a0 Sensor manufacturers work to optimize this tradeoff with each new generation of sensors. <\/p> <\/li>

  6. Output modes<\/strong>

    While each sensor typically has a \u201cstandard\u201d intended output, at full resolution, many sensors offer additional switchable outputs modes like Region of Interest (ROI), binning, or decimation.\u00a0 Such modes typically read out a defined subset of the pixels, at a higher frame rate, which can allow the same sensor and camera to serve two or more purposes.\u00a0 Example of binning would be a microscopy application whereby a binned image at high speed would be used to locate a target blob in a large field, then switch to full-resolution for a high-quality detail image.<\/p> <\/li><\/ol><\/div>\n\n\n\n

    For a more in depth review of these concepts, including helpful images and diagrams, please download the tech brief<\/a>.<\/strong><\/p>\n\n\n\n

    \"Download<\/a><\/figure><\/div>\n\n\n\n

    1st Vision\u2019s<\/a> sales engineers have an average of 20 years experience to assist in your camera selection.  Representing the largest portfolio<\/a> of industry leading brands in imaging components, we can help you design the optimal vision solution for your application.<\/p>\n","protected":false},"excerpt":{"rendered":"

    Image sensors are the key component of any camera and vision system.  This blog summarizes the key concepts of a tech brief addressing concepts essential to sensor performance relative to imaging applications. For a comprehensive analysis of the parameters, you may read the full tech brief. For a more in depth review of these concepts, … <\/p>\n

    Continue reading “Keys to Choosing the Best Image Sensor”<\/span><\/a><\/p>\n","protected":false},"author":10,"featured_media":1816,"comment_status":"closed","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8,142,26,61,104],"tags":[376,374,221,372,281,375,240,369,373,371,370,368,280,366],"class_list":["post-1791","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cameras","category-ccd","category-cmos","category-tutorial","category-white-paper","tag-aspect-ratio","tag-binning","tag-cmos","tag-dynamic-range","tag-global-shutter","tag-industrial-camera","tag-machine-vision","tag-optical-format","tag-pixel-size","tag-qe","tag-quantum-efficiency","tag-resolution","tag-rolling-shutter","tag-sensor"],"yoast_head":"\nKeys to Choosing the Best Image Sensor<\/title>\n<meta name=\"description\" content=\"Key image sensor specifications, parameters, or characteristics for machine vision and industrial cameras. 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Sensor sizes and lens sizes often have legacy names left over from TV standards now decades old, so we\u2019ll skip the details in this blog but invite the reader to read the linked tech brief or speak with a sales engineer, to insure the best fit.\"}],\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#schema-image-0ff9e36154c3f71e23755b9ff69f1a0c\",\"url\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/04\/AspectRatios.jpg\",\"contentUrl\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/04\/AspectRatios.jpg\",\"width\":511,\"height\":165}},{\"@type\":\"HowToStep\",\"url\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1616534226932\",\"name\":\"Quantum Efficiency and Dynamic Range:\",\"itemListElement\":[{\"@type\":\"HowToDirection\",\"text\":\"<br \/><strong>Quantum Efficiency (QE)<\/strong>: Sensors vary in their efficiency at converting photons to electrons, by sensor quality and at varying wavelengths of light, so some sensors are better for certain applications than others. <br \/><br \/> <br \/><br \/><strong>Dynamic Range (DR):<\/strong> Factors such as Full Well Capacity and Read Noise determine DR, which is the ratio of maximum signal to the minimum.\u00a0 The greater the DR, the better the sensor can capture the range of bright to dark gradations from the application scene.\"}],\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#schema-image-87870cf9e294c6e733a0f14f8a0488cd\",\"url\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/03\/QuantumEfficiency.jpg\",\"contentUrl\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/03\/QuantumEfficiency.jpg\",\"width\":369,\"height\":263,\"caption\":\"Typical QE response curve\"}},{\"@type\":\"HowToStep\",\"url\":\"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1616534117719\",\"name\":\"Optical parameters\",\"itemListElement\":[{\"@type\":\"HowToDirection\",\"text\":\"While some seemingly-color applications can in fact be solved more easily and cost-effectively with monochrome, in either case each silicon-based pixel converts light 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to Choosing the Best Image Sensor","mainEntityOfPage":{"@id":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#article"},"description":"While there are many aspects to consider, here we outline 6 key parameters:","step":[{"@type":"HowToStep","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1616534034432","name":"Physical parameters","itemListElement":[{"@type":"HowToDirection","text":"<br\/><strong>Resolution<\/strong>: The amount of information per frame (image) is the product of horizontal pixel count x by vertical pixel count y.\u00a0 While consumer cameras boast of resolution like car manufacturers tout horsepower, in machine vision one just needs enough resolution to solve the problem - but not more.\u00a0 Too much resolution leads to more sensor than you need, more bandwidth than you need, and more cost than you need.\u00a0 Takeaway: Match sensor resolution to optical resolution relative to the object(s) you must image.<br\/><br\/><strong>Aspect ratio<\/strong>: Whether 1:1, 3:2, or some other ratio, the optimal arrangement should correspond to the layout of your target\u2019s field of view, so as not to buy more resolution than is needed for your application. <br\/><br\/> <br\/><br\/><strong>Frame rate<\/strong>: If your target is moving quickly, you\u2019ll need enough images per second to \u201cfreeze\u201d the motion and to keep up with the physical space you are imaging.\u00a0 But as with resolution, one needs just enough speed to solve the problem, and no more, or you would over specify for a faster computer, cabling, etc.<br\/><br\/><strong>Optical format<\/strong>: One could write a thesis on this topic, but the key takeaway is to match the lens\u2019 projection of focused light onto the sensor\u2019s array of pixels, to cover the sensor (and make use of its resolution).\u00a0 Sensor sizes and lens sizes often have legacy names left over from TV standards now decades old, so we\u2019ll skip the details in this blog but invite the reader to read the linked tech brief or speak with a sales engineer, to insure the best fit."}],"image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#schema-image-0ff9e36154c3f71e23755b9ff69f1a0c","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/04\/AspectRatios.jpg","contentUrl":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/04\/AspectRatios.jpg","width":511,"height":165}},{"@type":"HowToStep","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1616534226932","name":"Quantum Efficiency and Dynamic Range:","itemListElement":[{"@type":"HowToDirection","text":"<br \/><strong>Quantum Efficiency (QE)<\/strong>: Sensors vary in their efficiency at converting photons to electrons, by sensor quality and at varying wavelengths of light, so some sensors are better for certain applications than others. <br \/><br \/> <br \/><br \/><strong>Dynamic Range (DR):<\/strong> Factors such as Full Well Capacity and Read Noise determine DR, which is the ratio of maximum signal to the minimum.\u00a0 The greater the DR, the better the sensor can capture the range of bright to dark gradations from the application scene."}],"image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#schema-image-87870cf9e294c6e733a0f14f8a0488cd","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/03\/QuantumEfficiency.jpg","contentUrl":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-content\/uploads\/2021\/03\/QuantumEfficiency.jpg","width":369,"height":263,"caption":"Typical QE response curve"}},{"@type":"HowToStep","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1616534117719","name":"Optical parameters","itemListElement":[{"@type":"HowToDirection","text":"While some seemingly-color applications can in fact be solved more easily and cost-effectively with monochrome, in either case each silicon-based pixel converts light (photons) into charge (electrons).\u00a0 Each pixel well has a maximum volume of charge it can handle before saturating.\u00a0 After each exposure, the degree of charge in a given pixel correlates to the amount of light that impinged on that pixel."}]},{"@type":"HowToStep","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1616534288992","name":"Rolling vs. Global shutter","itemListElement":[{"@type":"HowToDirection","text":"Most current sensors support global shutter, where all pixel rows are exposed at once, eliminating motion-induced blur.\u00a0 But the on-sensor electronics to achieve global shutter have certain costs associated, so for some applications it can still make sense to use rolling shutter sensors."}]},{"@type":"HowToStep","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1616534313305","name":"Pixel Size","itemListElement":[{"@type":"HowToDirection","text":"Just as a wide-mouth bucket will catch more raindrops than a coffee cup, a larger physical pixel will admit more photons than a small one.\u00a0 Generally speaking, large pixels are preferred.\u00a0 But that requires the expense of more silicon to support the resolution for a desired x by y array.\u00a0 Sensor manufacturers work to optimize this tradeoff with each new generation of sensors. "}]},{"@type":"HowToStep","url":"https:\/\/www.1stvision.com\/machine-vision-solutions\/2021\/04\/keys-to-choosing-the-best-image-sensor.html#how-to-step-1617118776951","name":"Output modes","itemListElement":[{"@type":"HowToDirection","text":"While each sensor typically has a \u201cstandard\u201d intended output, at full resolution, many sensors offer additional switchable outputs modes like Region of Interest (ROI), binning, or decimation.\u00a0 Such modes typically read out a defined subset of the pixels, at a higher frame rate, which can allow the same sensor and camera to serve two or more purposes.\u00a0 Example of binning would be a microscopy application whereby a binned image at high speed would be used to locate a target blob in a large field, then switch to full-resolution for a high-quality detail image."}]}],"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/posts\/1791","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/comments?post=1791"}],"version-history":[{"count":16,"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/posts\/1791\/revisions"}],"predecessor-version":[{"id":1827,"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/posts\/1791\/revisions\/1827"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/media\/1816"}],"wp:attachment":[{"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/media?parent=1791"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/categories?post=1791"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1stvision.com\/machine-vision-solutions\/wp-json\/wp\/v2\/tags?post=1791"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}