Structural Beauty: A Structure-based Approach to Quantifying the Beauty of an Image
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Abstract (arXiv)
To say that beauty is in the eye of the beholder means that beauty is largely subjective so varies from person to person. While the subjectivity view is commonly held, there is also an objectivity view that seeks to measure beauty or aesthetics in some quantitative manners. Christopher Alexander has long discovered that beauty or coherence highly correlates to the number of subsymmetries or substructures and demonstrated that there is a shared notion of beauty - structural beauty - among people and even different peoples, regardless of their faiths, cultures, and ethnicities. This notion of structural beauty arises directly out of living structure or wholeness, a physical and mathematical structure that underlies all space and matter. Based on the concept of living structure, this paper develops an approach for computing the structural beauty or life of an image (L) based on the number of automatically derived substructures (S) and their inherent hierarchy (H). To verify this approach, we conducted a series of case studies applied to eight pairs of images including Leonardo da Vinci's Mona Lisa and Jackson Pollock's Blue Poles. We discovered among others that Blue Poles is more structurally beautiful than the Mona Lisa, and traditional buildings are in general more structurally beautiful than their modernist counterparts. This finding implies that goodness of things or images is largely a matter of fact rather than an opinion or personal preference as conventionally conceived. The research on structural beauty has deep implications on many disciplines, where beauty or aesthetics is a major concern such as image understanding and computer vision, architecture and urban design, humanities and arts, neurophysiology, and psychology. Keywords: Life; wholeness; figural goodness; head/tail breaks; computer vision
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 1 of its 51 references that are in the map. First posted on arXiv 16 Apr 2021.
Builds on
1 of 51 references.
References · 1
- 2016Understanding and Mapping Natural Beautycited by 10
Built on by
Citing papers per year: 2023: 2; 2024: 0; 2025: 1.
3 papers.
- 2025CartoAgent: a multimodal large language model-powered multi-agent cartographic framework for map style transfer and evaluationcited by 4
- 2023Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Spacecited by 3
- 2023Recursive Segmentation Living Image: An eXplainable AI (XAI) Approach for Computing Structural Beauty of Images or the Livingness of Spacecited by 0
- 2025CartoAgent: a multimodal large language model-powered multi-agent cartographic framework for map style transfer and evaluation15 May 2025
- 2023Recursive Segmentation Living Image: An eXplainable AI (XAI) Approach for Computing Structural Beauty of Images or the Livingness of Space16 Oct 2023
- 2023Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Space4 Jan 2023