Hybrid lighting enhances color accuracy in DLP-based 3D imaging
Color accuracy is of immense importance in various fields, including biomedical applications, cosmetics, and multimedia. Achieving precise color measurements using diverse lighting sources is a persistent challenge. Recent advancements have resulted in the integration of LED-based Digital Light Proc...
- Autores:
-
Barrios, Erik
Pineda, Jesus
Romero, Lenny A.
Millan, María S.
Marrugo, Andres G.
- Tipo de recurso:
- Fecha de publicación:
- 2024
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12739
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12739
- Palabra clave:
- Color accuracy
Digital Light Processing
3D imaging
Fringe projection profilometry
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Hybrid lighting enhances color accuracy in DLP-based 3D imaging |
| title |
Hybrid lighting enhances color accuracy in DLP-based 3D imaging |
| spellingShingle |
Hybrid lighting enhances color accuracy in DLP-based 3D imaging Color accuracy Digital Light Processing 3D imaging Fringe projection profilometry |
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Hybrid lighting enhances color accuracy in DLP-based 3D imaging |
| title_full |
Hybrid lighting enhances color accuracy in DLP-based 3D imaging |
| title_fullStr |
Hybrid lighting enhances color accuracy in DLP-based 3D imaging |
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Hybrid lighting enhances color accuracy in DLP-based 3D imaging |
| title_sort |
Hybrid lighting enhances color accuracy in DLP-based 3D imaging |
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Barrios, Erik Pineda, Jesus Romero, Lenny A. Millan, María S. Marrugo, Andres G. |
| dc.contributor.author.none.fl_str_mv |
Barrios, Erik Pineda, Jesus Romero, Lenny A. Millan, María S. Marrugo, Andres G. |
| dc.subject.keywords.spa.fl_str_mv |
Color accuracy Digital Light Processing 3D imaging Fringe projection profilometry |
| topic |
Color accuracy Digital Light Processing 3D imaging Fringe projection profilometry |
| description |
Color accuracy is of immense importance in various fields, including biomedical applications, cosmetics, and multimedia. Achieving precise color measurements using diverse lighting sources is a persistent challenge. Recent advancements have resulted in the integration of LED-based Digital Light Processing (DLP) technology into many scanning devices for 3D imaging, often serving as the primary lighting source. However, such setups are susceptible to color-accuracy issues. Our study delves into DLP-based 3D imaging, specifically focusing on the use of hybrid lighting to enhance color accuracy. We presented an empirical dataset containing skin tone patches captured under various lighting conditions, including combinations and variations in indoor ambient light. A comprehensive qualitative and quantitative analysis of color differences (∆E 00 ) across the dataset was performed. Our results support the integration of DLP technology with supplementary light sources to achieve optimal color correction outcomes, particularly in skin tone reproduction, which has significant implications for biomedical image analysis and other color-critical applications. |
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2024 |
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2024-09-16T16:52:23Z |
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2024-09-16T16:52:23Z |
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2024-08 |
| dc.date.submitted.none.fl_str_mv |
2024-09-13 |
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Barrios, Erik & Pineda, Jesús & Romero, Lenny & Millán, María & Marrugo, Andrés. (2024). Hybrid lighting enhances color accuracy in DLP-based 3D imaging. Optical Engineering. 63. 10.1117/1.OE.63.8.083105. |
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https://hdl.handle.net/20.500.12585/12739 |
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10.1117/1.OE.63.8.083105. |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
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Barrios, Erik & Pineda, Jesús & Romero, Lenny & Millán, María & Marrugo, Andrés. (2024). Hybrid lighting enhances color accuracy in DLP-based 3D imaging. Optical Engineering. 63. 10.1117/1.OE.63.8.083105. 10.1117/1.OE.63.8.083105. Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/12739 |
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eng |
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eng |
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openAccess |
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19 páginas |
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application/pdf |
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Cartagena de Indias |
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Ingeniería |
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Optical Engineering No. 63 |
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Universidad Tecnológica de Bolívar |
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Barrios, Erikbb277699-e10e-4f85-982c-9a3b98acb515Pineda, Jesusa6827c4e-c14f-4dc1-ba8e-4c5b1cd055ebRomero, Lenny A.4e34aa8a-f981-4e1d-ae32-d45acb6abcf9Millan, María S.0a3267fb-ddb1-44c1-a0c3-66756561ae2aMarrugo, Andres G.3d6cd388-d48f-4669-934f-49ca4179f5422024-09-16T16:52:23Z2024-09-16T16:52:23Z2024-082024-09-13Barrios, Erik & Pineda, Jesús & Romero, Lenny & Millán, María & Marrugo, Andrés. (2024). Hybrid lighting enhances color accuracy in DLP-based 3D imaging. Optical Engineering. 63. 10.1117/1.OE.63.8.083105.https://hdl.handle.net/20.500.12585/1273910.1117/1.OE.63.8.083105.Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarColor accuracy is of immense importance in various fields, including biomedical applications, cosmetics, and multimedia. Achieving precise color measurements using diverse lighting sources is a persistent challenge. Recent advancements have resulted in the integration of LED-based Digital Light Processing (DLP) technology into many scanning devices for 3D imaging, often serving as the primary lighting source. However, such setups are susceptible to color-accuracy issues. Our study delves into DLP-based 3D imaging, specifically focusing on the use of hybrid lighting to enhance color accuracy. We presented an empirical dataset containing skin tone patches captured under various lighting conditions, including combinations and variations in indoor ambient light. A comprehensive qualitative and quantitative analysis of color differences (∆E 00 ) across the dataset was performed. Our results support the integration of DLP technology with supplementary light sources to achieve optimal color correction outcomes, particularly in skin tone reproduction, which has significant implications for biomedical image analysis and other color-critical applications.19 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Optical Engineering No. 63Hybrid lighting enhances color accuracy in DLP-based 3D imaginginfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Color accuracyDigital Light Processing3D imagingFringe projection profilometryCartagena de IndiasIngenieríaInvestigadoresA. G. Marrugo, F. Gao, and S. Zhang, “State-of-the-art active optical techniques for threedimensional surface metrology: a review [invited],” Journal of the Optical Society of America. A 37(9), B60–B77 (2020).H. Jiang, Z. Lin, Y. Li, et al., “Projection optical engine design based on tri-color leds and digital light processing technology,” Applied Optics 60(23), 6971–6977 (2021).R. Khan, Y. Yang, Q. Liu, et al., “Deep image enhancement for ill light imaging,” JOSA A 38(6), 827–839 (2021)D. Kalustova, V. Kornaga, A. Rybalochka, et al., “Color temperature tunable rgbw cluster with optimize color rendering and efficacy,” Optical Engineering 62(4), 045102–045102 (2023).S. Tanaka, A. Kakinuma, N. Kamijo, et al., “Auto white balance method using a pigmentation separation technique for human skin color,” Optical Review 24(1), 17–26 (2017)K. L. Hanlon, G. Wei, L. Correa-Selm, et al., “Dermoscopy and skin imaging light sources: a comparison and review of spectral power distribution and color consistency,” Journal of Biomedical Optics 27(8), 080902–080902 (2022).K. Xiao, J. M. Yates, F. Zardawi, et al., “Characterising the variations in ethnic skin colours: a new calibrated data base for human skin,” Skin Research and Technology 23(1), 21–29 (2017).M. Corbalan, M. S. Millan, and M. J. Yzuel, “Color measurement in standard CIELAB coordinates using a 3CCD camera: correction for the influence of the light source,” Optical Engineering 39(6), 1470–1476 (2000).M. D. Fairchild, Color appearance models, John Wiley & Sons (2013).A. Gijsenij, T. Gevers, and J. Van De Weijer, “Computational color constancy: Survey and experiments,” IEEE transactions on image processing 20(9), 2475–2489 (2011).J. Yang, M. Cai, and Z. Zhou, “Evolving convolution neural network by optimal regularization random vector functional link for computational color constancy,” Optical Engineering 61(10), 103102–103102 (2022)V. Agarwal, B. R. Abidi, A. Koschan, et al., “An overview of color constancy algorithms,” Journal of Pattern Recognition Research 1(1), 42–54 (2006)D. H. Foster, “Color constancy,” Vision Research 51(7), 674–700 (2011).D. Yung, K. Andy, R. T. Hsung, et al., “Comparison of the colour accuracy of a singlelens reflex camera and a smartphone camera in a clinical context,” Journal of Dentistry 137, 104681 (2023).J. Xu and S. Zhang, “Status, challenges, and future perspectives of fringe projection profilometry,” Optics and Lasers in Engineering 135, 106193 (2020)J. Pineda, R. Vargas, L. A. Romero, et al., “Robust automated reading of the skin prick test via 3d imaging and parametric surface fitting,” PloS one 14(10), e0223623 (2019).S. Han, I. Sato, T. Okabe, et al., “Fast spectral reflectance recovery using dlp projector,” International Journal of Computer Vision 110, 172–184 (2014).S. Voisin, D. L. Page, S. Foufou, et al., “Color influence on accuracy of 3d scanners based on structured light,” Proc. SPIE 6070, 72–80 (2006).H. Takiwaki, L. Overgaard, and J. Serup, “Comparison of narrow-band reflectance spectrophotometric and tristimulus colorimetric measurements of skin color: Twenty-three anatomical sites evaluated by the dermaspectrometer® and the chroma meter cr-200®,” Skin Pharmacology and Physiology 7(4), 217–225 (1994).A. R. Matias, M. Ferreira, P. Costa, et al., “Skin colour, skin redness and melanin biometric measurements: comparison study between antera® 3d, mexameter® and colorimeter®,” Skin Research and Technology 21(3), 346–362 (2015).S. Tedla, Y. Wang, M. Patel, et al., “Analyzing color imaging failure on consumer-grade cameras,” JOSA A 39(6), B21–B27 (2022)W. Chen, Z. Huang, Q. Liu, et al., “Evaluating the color preference of lighting: the light booth matters,” Optics Express 28(10), 14874–14883 (2020).R. Roa, R. Huertas, M. A. Lopez- ´ Alvarez, ´ et al., “A comparison between illuminants and light-source simulators,” Optica Pura y Aplicada 41(3), 291–300 (2008)C. C. Cooksey, D. W. Allen, and B. K. Tsai, “Reference data set of human skin reflectance,” J. Res. Nat. Inst. Standards Technol. 122, 1–5 (2017).C. S. McCamy, H. Marcus, and J. G. Davidson, “A color-rendition chart,” J. App. Photog. Eng 2(3), 95–99 (1976).E. Kirchner, C. van Wijk, H. van Beek, et al., “Exploring the limits of color accuracy in technical photography,” Heritage Science 9(1), 1–13 (2021).H. Wannous, Y. Lucas, S. Treuillet, et al., “Improving color correction across camera and illumination changes by contextual sample selection,” Journal of Electronic Imaging 21(2), 023015 (2012).M. Luo and R. Hunt, “The structure of the cie 1997 colour appearance model (ciecam97s),” Color Research & Application: Endorsed by Inter-Society Color Council, The Colour Group (Great Britain), Canadian Society for Color, Color Science Association of Japan, Dutch Society for the Study of Color, The Swedish Colour Centre Foundation, Colour Society of Australia, Centre Franc¸ais de la Couleur 23(3), 138–146 (1998).X. Li, G. Hou, L. Tan, et al., “A hybrid framework for underwater image enhancement,” IEEE Access 8, 197448–197462 (2020).G. Sharma, W. Wu, and E. N. Dalal, “The ciede2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations,” Color Research and Application 30(1), 21–30 (2005)R. Vargas, A. G. Marrugo, S. Zhang, et al., “Hybrid calibration procedure for fringe projection profilometry based on stereo vision and polynomial fitting,” Applied Optics 59(13), D163–D169 (2020).R. Vargas, L. A. Romero, S. Zhang, et al., “Pixel-wise rational model for a structured light system,” Optics Letters 48(10), 2712–2715 (2023).S. 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