Cognitive Computing for Understanding and Restoring Color in Renaissance Art
In this article, for the first time on this topic, we analyze the historical color palettes of Renaissance oil paintings by using machine-learning methods and digital images. Our work has two main parts: we collect data on their historical color palettes and then use machine learning to predict the...
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| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/9/5/113 |
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| author | Artyom M. Grigoryan Sos S. Agaian Shao Liu |
| author_facet | Artyom M. Grigoryan Sos S. Agaian Shao Liu |
| author_sort | Artyom M. Grigoryan |
| collection | DOAJ |
| description | In this article, for the first time on this topic, we analyze the historical color palettes of Renaissance oil paintings by using machine-learning methods and digital images. Our work has two main parts: we collect data on their historical color palettes and then use machine learning to predict the original colors of paintings. This model studies color ratios, enhancement levels, symbolic meanings, and historical records. It looks at key colors, measures their relationships, and learns how they have changed. The main contributions of this work are as follows: (i) we develop a model that predicts a painting’s original color palette based on multiple factors, such as the color ratios and symbolic meanings, and (ii) we propose a framework for using cognitive computing tools to recover the original colors of historical artworks. This helps us to rediscover lost emotional and cultural details. |
| format | Article |
| id | doaj-art-6fd5fd41444b47bf9985b843cc055140 |
| institution | OA Journals |
| issn | 2504-2289 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj-art-6fd5fd41444b47bf9985b843cc0551402025-08-20T01:56:25ZengMDPI AGBig Data and Cognitive Computing2504-22892025-04-019511310.3390/bdcc9050113Cognitive Computing for Understanding and Restoring Color in Renaissance ArtArtyom M. Grigoryan0Sos S. Agaian1Shao Liu2Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USAComputer Science Department, College of Staten Island, Staten Island, NY 10314, USAComputer Science Department, College of Staten Island, Staten Island, NY 10314, USAIn this article, for the first time on this topic, we analyze the historical color palettes of Renaissance oil paintings by using machine-learning methods and digital images. Our work has two main parts: we collect data on their historical color palettes and then use machine learning to predict the original colors of paintings. This model studies color ratios, enhancement levels, symbolic meanings, and historical records. It looks at key colors, measures their relationships, and learns how they have changed. The main contributions of this work are as follows: (i) we develop a model that predicts a painting’s original color palette based on multiple factors, such as the color ratios and symbolic meanings, and (ii) we propose a framework for using cognitive computing tools to recover the original colors of historical artworks. This helps us to rediscover lost emotional and cultural details.https://www.mdpi.com/2504-2289/9/5/113color symbologycolor ratiocolor paletterenaissance oil paintingscolor image enhancementalpha-rooting |
| spellingShingle | Artyom M. Grigoryan Sos S. Agaian Shao Liu Cognitive Computing for Understanding and Restoring Color in Renaissance Art Big Data and Cognitive Computing color symbology color ratio color palette renaissance oil paintings color image enhancement alpha-rooting |
| title | Cognitive Computing for Understanding and Restoring Color in Renaissance Art |
| title_full | Cognitive Computing for Understanding and Restoring Color in Renaissance Art |
| title_fullStr | Cognitive Computing for Understanding and Restoring Color in Renaissance Art |
| title_full_unstemmed | Cognitive Computing for Understanding and Restoring Color in Renaissance Art |
| title_short | Cognitive Computing for Understanding and Restoring Color in Renaissance Art |
| title_sort | cognitive computing for understanding and restoring color in renaissance art |
| topic | color symbology color ratio color palette renaissance oil paintings color image enhancement alpha-rooting |
| url | https://www.mdpi.com/2504-2289/9/5/113 |
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