Manuscript received September 18, 2025; revised October 10, 2025; accepted November 10, 2025; published 26, 2026.

Abstract—Designing websites to meet user and client expectations often requires repeated refinement cycles, making the process time-consuming and resource-intensive. This study proposes an automated classification system that categorizes real-world websites based on their salient structural design features to support data-driven automatic website generation. The system integrates Self-Organizing Maps (SOMs) with a novel image-processing pipeline that combines edge detection, gradient analysis, and morphological filtering and image smoothing to extract structural wireframe layouts from website screen captures. Experiments were conducted on three datasets: manually created wireframes, screen captures of top 100 websites, and screen captures of top 1500 websites ranked by SimilarWeb. The analysis revealed seven representative layout archetypes: dashboard interfaces, simple information pages, fixed-width product grids, informational pages with sidebars, basic search interfaces, multi-section content layouts, and tabular data interfaces. The classification quality was evaluated using topographic error, quantization error, Silhouette coefficient, and Davies-Bouldin index, demonstrating consistent and meaningful clustering. Our findings highlight the potential of SOM-based clustering for automatic website template generation, offering a scalable and data-driven foundation for design automation and frontend prototyping.

Keywords—website structure analysis, automatic website generation, web design clustering, salient design features, self-organizing maps

Cite: Thisaranie Kaluarachchi, Sumedhe Dissanayake, and Manjusri Wickramasinghe, "Clustering Websites by Salient Design Features," Journal of Image and Graphics, Vol. 14, No. 2, pp. 230-258, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC-BY-4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.