Image Analysis 0f Maka’if Bikomi Lokal Traditional Fabric Motifs Based On Otsu Thresholding For Pattern Identifikasi

Abstract

Maka’if is a traditional woven motif originating from the Dawan Miomafo community in North Central Timor, East Nusa Tenggara, Indonesia. This study investigates the segmentation and pattern analysis of the Maka’if motif using digital image processing techniques, specifically thresholding and Otsu thresholding. The dataset consisted of six original motif images that were augmented through rotational transformation to produce 30 image samples. The research process included image acquisition, preprocessing, grayscale conversion, filtering, segmentation, and performance evaluation using Mean Square Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). Experimental results indicate that conventional thresholding was able to identify the basic motif structure but produced higher noise and inconsistent segmentation due to the use of a fixed threshold value. In contrast, Otsu thresholding automatically determined optimal threshold values based on image histogram distribution, resulting in clearer motif structures, lower noise, and more stable segmentation. The analysis revealed repetitive diamond-shaped geometric patterns combined with spiral and diagonal micro-ornaments as the main visual characteristics of the Maka’if motif. The proposed approach demonstrates the potential of digital image processing for the documentation, standardization, and preservation of traditional woven cultural heritage.