Shape analysis for digital representation of East Asian silk patterns

Thesis: S.M. in Architecture Studies, Massachusetts Institute of Technology, Department of Architecture, 2018. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 58-61). === This thesis examines the East Asian geometric silk pattern. Despite its long history of...

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Bibliographic Details
Main Author: Koh, Hunmin
Other Authors: Takehiko Nagakura.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2018
Subjects:
Online Access:http://hdl.handle.net/1721.1/118513
Description
Summary:Thesis: S.M. in Architecture Studies, Massachusetts Institute of Technology, Department of Architecture, 2018. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 58-61). === This thesis examines the East Asian geometric silk pattern. Despite its long history of use in traditional architecture as an ornamental element in Korea and China, a little attempt was made to understand its geometric construction. Also, the connection between the silk patterns in two countries are often neglected because of the lack of systematic archiving. I first present the currently existing examples of silk patterns in Korea and China. Through a comparative analysis, I identify that the pattern is a shared heritage of the region and proses that more holistic approach is required to understand its relation with geometric patterns from other cultures. One of the approach is symmetry analysis, a method used in archeology to identify relevance in material culture between two adjacent cultural groups. Subsequently, I present shape analysis of existing sixfold symmetry silk patterns and argue that the stacking order of basic motifs plays an important role in design of the majority of silk patterns. I devised a symbolic notation system to identify different stacking order between different designs. Based on the analysis, I introduce an automated pattern generator which creates patterns with a specific symmetry in batches. The produced images can be used to train a symmetry classifier based on a machine learning model. I discuss possible implementations of the pattern generator and the symmetry classifier model and outline future development and challenges. === by Hunmin Koh. === S.M. in Architecture Studies