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Clustering Letters in The Metal Inscription Using ANFIS Filter

Author(s): Susijanto Tri Rasmana | Yoyon K. Suprapto | Ketut E. Purnama

ISSN 1693-6930

Volume: 11;
Issue: 3;
Date: 2013;
Original page

Keywords: Metal inscription | Clustering | CIELab | ANFIS

Ancient inscriptions are historical records of the past were made on stone or metal media. Currently many ancient inscriptions were damaged because for too long buried in the ground. This research is the first step to repairing the damaged inscription using Image processing. Efforts to restoration using ANFIS clustering are an early stage to perform segmentation letters in the inscription. The Results of clustering ANFIS method is compared to the spatial fuzzy clustering method (SFCM). Measuring the performance of clustering is done by measuring root mean square error (RMSE). From RMSE measurements, the average values ??obtained for the measurement of clustering with ANFIS method smaller 21.80% compared to SFCM. This means there is an increase in clustering performance with ANFIS method compared to SFCM. Even so further efforts are needed to improve the clustering quality of metal inscription.
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