Digitization and recognition of Jacquard cards for textile design preservation

Abstract This paper introduces an advanced, structured approach to preserving textile design, specifically targeting the intricate silk motifs woven using Jacquard machines in the textile industry. Traditional Jacquard machines utilize perforated cards, where specific hole patterns guide needle movements to create complex designs. Due to deterioration over time, these cards need replacement to maintain design integrity, making digitization essential for preserving cultural heritage. To address this need, we developed a multi-step, computer vision-based method that extracts design information from images of these Jacquard cards. The process involves 1) segmenting each card from images, 2) identifying and locating hole patterns, 3) refining hole detection through interpolation and statistical validation, and 4) post-processing for error detection and correction. This results in highly accurate, vectorized digital files, which can be replicated using laser technology to produce new cards. Additionally, an algorithm generates corresponding fabric patterns directly from the digital designs. This systematic approach not only facilitates the preservation and replication of historic silk motifs but also supports ongoing innovation in textile design.