Citra Kain Tenun Nusa Tenggara Timur (Woven Fabrics Nusa Tenggara Timur Image)

The recognition of woven fabrics through image processing has a high value in preserving cultural heritage and assisting in identifying and classifying traditional textile products. To this end, this study proposes an approach that utilizes a Decision Tree (DT) to recognize images of woven fabrics typical of East Nusa Tenggara. DT's effectiveness in high-dimensional data classification makes it an ideal tool for modeling unique patterns in woven fabric drawings. Our dataset consists of different types of East Nusa Tenggara woven fabrics, and experimental results show the accuracy of our proposed approach in recognizing these fabrics, achieving promising success rates in the classification of complex motifs and patterns. These findings significantly contribute to the development of automated systems for identifying and documenting traditional woven fabrics, which in turn can support cultural preservation initiatives and local industrial growth in East Nusa Tenggara.