AI-Guided Concept to Design Output: A Comparative Visual Analysis Based on SSIM, Histogram, and LBP in an Interior Architecture Studio

Year 2025, Volume: 7 Issue: 1, 217 - 233, 10.07.2025

Türkan Harmanbaşı

https://doi.org/10.46474/jds.1670238

Abstract

Artificial intelligence (AI) has rapidly become a transformative force in design disciplines, including interior architecture. With the increasing integration of AI tools into the design process, interior architecture education faces new pedagogical opportunities and challenges. This study examines how second-year interior architecture students utilized artificial intelligence (AI)-supported visual generation tools during the conceptualization and development of their design projects, and investigates the impact of these tools on creative processes within the context of the 'Interior Architecture Project I' design studio conducted at Istanbul Sabahattin Zaim University.

Ten second-year interior architecture students participated in a semester-long project focusing on the adaptive reuse of the historic Kibrithane Building, redesigned as a restaurant interior. At the beginning of the course, students generated concept visuals using AI tools such as Midjourney, Canva and Bing, etc. These images were based on their self-authored prompts and were intended not as final design templates but as visual stimuli to encourage reflective engagement and conceptual development. Students developed functional layouts, material, color strategies, and 3D models based on their AI-inspired concepts throughout the semester.

A comparative analysis was conducted between the AI-generated images and the final student designs using qualitative observations and quantitative image analysis methods: Structural Similarity Index (SSIM), Histogram Comparison, and Local Phase Descriptor (LPD). The evaluation focused on four key criteria: form, material, color, and spatial organization. The findings emphasize that AI tools, when used reflectively, act as creative catalysts rather than prescriptive design solutions. The study concludes that AI integration in design studios can support conceptual exploration, foster critical thinking, and maintain students’ creative autonomy. It also recommends that educators guide students in interpreting and transforming AI outputs through aesthetic, functional, and contextual reasoning rather than applying them directly. This research contributes to the evolving discourse on AI in design education by highlighting its pedagogical potential and offering a framework for structured, critical integration within interior architecture curricula.

Keywords

Artificial intelligence , Interior architecture studio , AI-generated concepts , Creative process , Artificial intelligence in design education

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