cultural significance. Among the various Batik techniques, Batik tulis klowong, which employs wax outlines to
form intricate motifs, is critical for preserving the authenticity and quality of traditional Batik. However, a major
research gap exists in the form of inefficient and inconsistent manual defect detection, which hampers quality
control in Batik production. This limitation highlights the need for a more reliable and automated inspection
system, motivating the current study to develop a solution that addresses these challenges. This study presents an
automated defect detection system utilizing normalized cross-correlation (NCC) and integral image techniques
combined with adaptive thresholding. Focusing on the red color channel, the system’s performance is evaluated
using false positive rate (FPR), sensitivity, and accuracy. The results demonstrate that the integral image method
surpasses NCC, achieving an FPR of 1.92%, sensitivity of 86.18%, and accuracy of 96.82%, while significantly
reducing processing time to 1.019 seconds compared to NCC’s 6.116 seconds.These findings indicate that the
integral image approach provides a more efficient and accurate solution for Batik tulis klowong quality assessment,
benefiting the Batik industry by enhancing production processes, lowering operational costs, and contributing to
the preservation of Indonesia’s cultural heritage.
Rumpun Ilmu
Teknik Industri
Bahasa Asli/Original Language
English
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
8-s2_0-S2590123025002129-main.pdf
[PAK] Full Dokumen
2
Comparative study of integral image and normalized cross-correlation methods for defect detection on Batik klowong fabric.pdf
