From Clay to Code: Typological and Material Reasoning in AI Interpretations of Iranian Pigeon Towers

Fuente: arXiv
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Auteurs principaux: Pishahang, Abolhassan, Badiei, Maryam
Format: Preprint
Publié: 2025
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author Pishahang, Abolhassan
Badiei, Maryam
author_facet Pishahang, Abolhassan
Badiei, Maryam
contents This study investigates how generative AI systems interpret the architectural intelligence embedded in vernacular form. Using the Iranian pigeon tower as a case study, the research tests three diffusion models, Midjourney v6, DALL-E 3, and DreamStudio based on Stable Diffusion XL (SDXL), across three prompt stages: referential, adaptive, and speculative. A five-criteria evaluation framework assesses how each system reconstructs typology, materiality, environment, realism, and cultural specificity. Results show that AI reliably reproduces geometric patterns but misreads material and climatic reasoning. Reference imagery improves realism yet limits creativity, while freedom from reference generates inventive but culturally ambiguous outcomes. The findings define a boundary between visual resemblance and architectural reasoning, positioning computational vernacular reasoning as a framework for analyzing how AI perceives, distorts, and reimagines traditional design intelligence.
format Preprint
id arxiv_https___arxiv_org_abs_2601_00029
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle From Clay to Code: Typological and Material Reasoning in AI Interpretations of Iranian Pigeon Towers
Pishahang, Abolhassan
Badiei, Maryam
Artificial Intelligence
Computer Vision and Pattern Recognition
This study investigates how generative AI systems interpret the architectural intelligence embedded in vernacular form. Using the Iranian pigeon tower as a case study, the research tests three diffusion models, Midjourney v6, DALL-E 3, and DreamStudio based on Stable Diffusion XL (SDXL), across three prompt stages: referential, adaptive, and speculative. A five-criteria evaluation framework assesses how each system reconstructs typology, materiality, environment, realism, and cultural specificity. Results show that AI reliably reproduces geometric patterns but misreads material and climatic reasoning. Reference imagery improves realism yet limits creativity, while freedom from reference generates inventive but culturally ambiguous outcomes. The findings define a boundary between visual resemblance and architectural reasoning, positioning computational vernacular reasoning as a framework for analyzing how AI perceives, distorts, and reimagines traditional design intelligence.
title From Clay to Code: Typological and Material Reasoning in AI Interpretations of Iranian Pigeon Towers
topic Artificial Intelligence
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2601.00029