<![CDATA[Indonesia comprises a diverse array of ethnic groups and cultures. Each ethnic group has unique carving motifs rich in philosophical meaning. Toraja motifs are among the most distinctive in the world. These motifs are often found in traditional houses, textiles, and architectural ornaments. However, people's understanding of the symbolic value of these carvings remains limited, thereby risking cultural erosion. This study aims to recognize Toraja carving motifs using digital image processing, specifically through the extraction of Gray Level Co-occurrence Matrix (GLCM) texture features, which include contrast, correlation, energy, and homogeneity at 0° orientation. The Toraja carving dataset was processed through preprocessing, feature extraction, and thresholding-based classification stages. This study contributes to the combination of GLCM and thresholding that can improve accuracy while providing a computationally efficient solution for traditional motif pattern recognition. Experimental results show that thresholds of 0.002 and 0.004 produce recognition accuracies of 100% and 82%, respectively.]]>
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