Quantifying subtle color transitions in Mark Rothko's abstract paintings through K-means clustering and Delta E analysis

• This study applies color analysis to Mark Rothko's abstract paintings. • K-means clustering and Delta E metrics are used to examine color compositions. • Subtle color transitions and composition depth are quantified. • The findings offer insights into Rothko's complex use of color. • This approach highlights how image analysis expands art knowledge. A pivotal figure in American art, Mark Rothko, produced paintings characterized by large, gently blended color fields, challenging traditional perceptions of simplicity and complexity within abstract art. This research investigates the application of computational color analysis techniques to Mark Rothko's abstract paintings, focusing on his unique approach to color as a means of expression. Utilizing K-means clustering and Delta E metrics, this study systematically analyzes the color compositions in Rothko's paintings, allowing for a detailed examination of color relationships and transitions. By quantifying color variations and identifying subtle hue variations, the manuscript aims to examine the underlying structures that contribute to the global resonance of Rothko's art. The findings offer valuable insights into the artist's methodology, highlighting the significance of color dynamics in shaping viewer experiences, while also enhancing understanding of art through a mathematical and computational lens. The analyses also provide a framework of color dynamics and material changes, enabling more accurate preservation, and restoration of artworks over time, ensuring their integrity and original visual impact are maintained.