<![CDATA[The cultural significance of Indonesian woven fabrics intricately patterned by hand is dampened by slow, expensive automatic motif recognition processes. This research aimed to build a system that automatically detects and identifies motifs in textiles using image processing in MATLAB. The steps included collecting and preprocessing images, constructing a dataset, performing image comparison and similarity measurements, and color analysis. A dataset containing images of woven fabrics from different regions of Indonesia was created which included region-specific motifs. Images were enhanced through preprocessing and motif features were extracted through preprocessing. Determining the degree of correlation enabled features to be compared with the dataset, while color analysis tailored color characterization to specific motifs. The algorithm was able to detect motifs accurately using dataset references. The resemblance of motifs was greatly enhanced using color analysis. The approach is efficient and reliable for technology-aided culture preservation compared with manual methods. The analysis confirmed advanced MATLAB automation systems broadened opportunities in motif recognition within traditional textiles beyond automated processes, emphasizing the need for a detailed exploration of textile research projects]]>
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