[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-565508-105":53,"doc-detail-565508-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","validation-of-skin-tone-test-charts-with-real-human-data","Validation of Skin Tone Test Charts with Real Human Data","","Photographic test charts for measuring color accuracy in cameras historically use limited skin tones as uniform patches, which fail to represent the full diversity of human skin and do not evaluate modern automatic exposure, white balance, and focus (3A) behavior commonly driven by facial detection. A study photographed participants across the Monk Skin Tone Scale, reproduced scenes with high-resolution inkjet prints, and compared subject and chart captures via CIEDE2000 differences across face regions. Findings indicate sufficiently wide-gamut printed face charts enable repeatable lab benchmarking for color accuracy and 3A behavior.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/validation-of-skin-tone-test-charts-with-real-human-data/565508/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/validation-of-skin-tone-test-charts-with-real-human-data/565508.png","ImageObject",442,249,{"name":88,"@type":89},"Supernature","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-19","2026-10-13",true,{"@type":98,"interactionType":99,"userInteractionCount":73},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"Why are uniform-patch skin tone charts insufficient for modern camera testing?","Question",{"text":108,"@type":109},"They do not cover the full range of human skin tones and cannot evaluate scene-dependent processing such as automatic exposure, white balance, and focus (3A) triggered by face detection.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"How was the printed skin tone face chart study conducted?",{"text":113,"@type":109},"Participants with skin tones spanning the Monk Skin Tone Scale were photographed under controlled lighting, then scenes were reproduced using high-resolution inkjet prints of each participant.",{"name":115,"@type":106,"acceptedAnswer":116},"What metric was used to compare real human captures with printed charts?",{"text":117,"@type":109},"CIEDE2000 color difference was computed for regions of interest across the participant’s face in each scene.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},565508,1792438285,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":8,"category_name":11,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":73,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":135,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":76},962093270004,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","[https://doi.org/10.2352/EI.2026.38..IQSP-247](https://doi.org/10.2352/EI.2026.38..IQSP-247)[ ](https://doi.org/10.2352/EI.2026.38..IQSP-247)©2026 Society for Imaging Science and Technology  \nValidation of Skin Tone Test Charts with Real Human Data  \nMegan Borek1, Amelia Limbocker1, Ellis Monk2  \n1Imatest LLC; Boulder, Colorado, USA  \n2Harvard University; Cambridge, Massachusetts, USA  \nAbstract  \nPhotographic test charts for measuring color accuracy in cameras have historically included a limited number of skin tones, typically in the form of uniform color patches. Such charts are not representative of the wide range of skin tones found in humans, and do not test the behavior of modern automatic exposure, white balance, and focus (3A) algorithms that are commonly driven by facial detection in today’s digital consumer cameras. We built upon our previous work on the development of printed skin tone charts featuring detectable faces by conducting a study with human participants whose skin tones approximately span the Monk Skin Tone Scale. Participants were photographed under a series of controlled lighting conditions, and each scene was then reproduced using a high-resolution inkjet print of the participant. Corresponding captures of the human subjects and the printed charts were quantitatively compared by calculating the CIEDE2000 color difference for regions of interest across the subject’s face in the scene. This analysis evaluates how printed skin tones behave across exposure settings and lighting conditions relative to real skin, with the goal of determining whether printed charts provide a suitable solution for repeatable, lab-based image quality testing in face-present scenes. While not intended to replace final field testing with real human subjects, results indicate that face charts printed with sufficiently wide-gamut printers can provide an effective solution for lab testing and benchmarking of color accuracy and 3A behavior in a controlled and repeatable manner.  \nBackground  \nThe use of skin tones in image quality testing dates back to film color calibration in the mid-20th century. One of the first mainstream examples was Kodak’s use of the “Shirley Card”, introduced in the 1950s, which featured a female model with a light skin tone positioned with colored objects, clothing, or patches on a reference print used by photo labs to calibrate printing machines [1] . These remained the standard until the first multi-racial Shirley Card was introduced more than 40 years later in 1995 [1] . As a result, darker skin tones and objects were often poorly rendered, lacking contrast and detail, appearing underexposed, or exhibiting hue shifts.  \nAlthough the use of the Shirley card declined with the rise of digital photography, many of these issues have persisted in modern imaging systems, in part due to the continued lack of camera testing and image signal processor (ISP) tuning for scenes containing subjects with a wide range of skin tones.  \nThe Calibrite ColorChecker, originally introduced as the Macbeth ColorChecker in 1976, is a classic 24-patch color target that remains widely used in modern image quality testing for measuring color reproduction accuracy and performing color correction [2] . The chart includes only two skin tone patches (light and dark), representing a limited subset of the wide range ofmelanin content and undertones found in human skin. This leaves the lightest, darkest, and many mid-tones underrepresented in the color  \ncharacterization and calibration process. Wider-gamut charts, such as the 140-patch ColorChecker Digital SG, have been introduced for testing digital cameras and contain a larger variety of skin tones, but remain less widely used than the classic ColorChecker chart.  \nIn the past decade, increased attention has been given to improving skin tone reproduction in consumer cameras across abroader range of tones. Examples include Google’s Real Tone technology in Pixel smartphones [3], image q","cbCaimPvavk5PGyL","https://ap.wps.com/l/cbCaimPvavk5PGyL","pdf",1323272,7,"English","# Abstract\n# Background\n# Related Work\n# Methods and Evaluation\n# Results and Discussion","[{\"question\":\"Why are uniform-patch skin tone charts insufficient for modern camera testing?\",\"answer\":\"They do not cover the full range of human skin tones and cannot evaluate scene-dependent processing such as automatic exposure, white balance, and focus (3A) triggered by face detection.\"},{\"question\":\"How was the printed skin tone face chart study conducted?\",\"answer\":\"Participants with skin tones spanning the Monk Skin Tone Scale were photographed under controlled lighting, then scenes were reproduced using high-resolution inkjet prints of each participant.\"},{\"question\":\"What metric was used to compare real human captures with printed charts?\",\"answer\":\"CIEDE2000 color difference was computed for regions of interest across the participant’s face in each scene.\"}]","Validation of Skin Tone Test Charts with Real Human Data | PDF",1791855637]