Optimizing Correction Factors on Color Differences for Automotive Painting Services
Currently, the automotive sector is showing increased demands regarding the color of cars in general, but especially the quality and the time of painting, in particular. Companies working in this industry, especially in specialized painting services, must perform work of impeccable quality in the sh...
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MDPI AG
2024-12-01
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| author | Emilia Corina Corbu Anne-Marie Nitescu Eduard Edelhauser |
| author_facet | Emilia Corina Corbu Anne-Marie Nitescu Eduard Edelhauser |
| author_sort | Emilia Corina Corbu |
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| description | Currently, the automotive sector is showing increased demands regarding the color of cars in general, but especially the quality and the time of painting, in particular. Companies working in this industry, especially in specialized painting services, must perform work of impeccable quality in the shortest possible time in order to be efficient. Color differences that appear in different areas of the car result from the use of different formulas for obtaining color. These differences can be reduced by using correction factors that are established for the colors in the partial or total painting process of cars. There are several factors that lead to settings that are not verified by the real color and, therefore, contribute to incorrect color results and also to high and unnecessary repair costs. In this study, the authors aimed to optimize the values of the correction factors applicable in the automotive industry, based on a set of 135 measurements performed with a BYK Gardner spectrophotometer, in order to minimize color differences. Through this study, authors have also aimed to find out how the color-identification process can be streamlined with the smallest possible tolerances by optimally adjusting the correction factors and by identifying the factors that influence the color-reading and identification process. A total of 85 pairs of samples were used for the DS1 (data set) and 53 pairs of samples for the DS2 (data set); these samples were used in the visual experiments for testing the performance of two color-differentiation formulas. The first part of the research aimed to investigate the visual perception of the painted cars in terms of differences in brightness, chroma and hue, data that were used to optimize the formulas used for color differences. Finally, authors have estimated the closest color variant to the objective color by optimizing the correction factors and thus achieving the efficiency of the color-identification process and the whole painting-identification process. |
| format | Article |
| id | doaj-art-6f498328605a4dd3a85d7d48a74136ef |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
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| spelling | doaj-art-6f498328605a4dd3a85d7d48a74136ef2025-08-20T02:43:50ZengMDPI AGSensors1424-82202024-12-012424821310.3390/s24248213Optimizing Correction Factors on Color Differences for Automotive Painting ServicesEmilia Corina Corbu0Anne-Marie Nitescu1Eduard Edelhauser2Department of Mathematics and Informatics, University of Petrosani, 332003 Petrosani, RomaniaDepartment of Mathematics and Informatics, University of Petrosani, 332003 Petrosani, RomaniaDepartment of Management and Industrial Engineering, University of Petrosani, 332003 Petrosani, RomaniaCurrently, the automotive sector is showing increased demands regarding the color of cars in general, but especially the quality and the time of painting, in particular. Companies working in this industry, especially in specialized painting services, must perform work of impeccable quality in the shortest possible time in order to be efficient. Color differences that appear in different areas of the car result from the use of different formulas for obtaining color. These differences can be reduced by using correction factors that are established for the colors in the partial or total painting process of cars. There are several factors that lead to settings that are not verified by the real color and, therefore, contribute to incorrect color results and also to high and unnecessary repair costs. In this study, the authors aimed to optimize the values of the correction factors applicable in the automotive industry, based on a set of 135 measurements performed with a BYK Gardner spectrophotometer, in order to minimize color differences. Through this study, authors have also aimed to find out how the color-identification process can be streamlined with the smallest possible tolerances by optimally adjusting the correction factors and by identifying the factors that influence the color-reading and identification process. A total of 85 pairs of samples were used for the DS1 (data set) and 53 pairs of samples for the DS2 (data set); these samples were used in the visual experiments for testing the performance of two color-differentiation formulas. The first part of the research aimed to investigate the visual perception of the painted cars in terms of differences in brightness, chroma and hue, data that were used to optimize the formulas used for color differences. Finally, authors have estimated the closest color variant to the objective color by optimizing the correction factors and thus achieving the efficiency of the color-identification process and the whole painting-identification process.https://www.mdpi.com/1424-8220/24/24/8213color differencesensory analysishuman visual perceptionimage analysisCIELABoptimization |
| spellingShingle | Emilia Corina Corbu Anne-Marie Nitescu Eduard Edelhauser Optimizing Correction Factors on Color Differences for Automotive Painting Services Sensors color difference sensory analysis human visual perception image analysis CIELAB optimization |
| title | Optimizing Correction Factors on Color Differences for Automotive Painting Services |
| title_full | Optimizing Correction Factors on Color Differences for Automotive Painting Services |
| title_fullStr | Optimizing Correction Factors on Color Differences for Automotive Painting Services |
| title_full_unstemmed | Optimizing Correction Factors on Color Differences for Automotive Painting Services |
| title_short | Optimizing Correction Factors on Color Differences for Automotive Painting Services |
| title_sort | optimizing correction factors on color differences for automotive painting services |
| topic | color difference sensory analysis human visual perception image analysis CIELAB optimization |
| url | https://www.mdpi.com/1424-8220/24/24/8213 |
| work_keys_str_mv | AT emiliacorinacorbu optimizingcorrectionfactorsoncolordifferencesforautomotivepaintingservices AT annemarienitescu optimizingcorrectionfactorsoncolordifferencesforautomotivepaintingservices AT eduardedelhauser optimizingcorrectionfactorsoncolordifferencesforautomotivepaintingservices |