ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN (STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR)
| Main Authors: | , Nicodemus Mardanus Setiohardjo, , Drs. Agus Harjoko, M.Sc, Ph.D |
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| Format: | Thesis NonPeerReviewed |
| Terbitan: |
[Yogyakarta] : Universitas Gadjah Mada
, 2013
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| Subjects: | |
| Online Access: |
https://repository.ugm.ac.id/125977/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=66159 |
Daftar Isi:
- Indonesia has many culture in form of traditional fabrics, one of them is woven fabric from Nusa Tenggara Timur (NTT). Each NTT ethnic has motif characteristic which is a manifestation of daily life, culture and the belief of local community. For NTT woven fabric observers, the origin of a woven fabric can be known from the motif. But its difficult to identified the origin of a woven fabrics because it is hard to define the characteristics of woven fabric motif from a region and the diversities both of the motifs and the color compositions. Texture analysis is the image analysis technique based on the assumption that an image was formed by pixels intensity variations, both gray and color images. Woven fabric motif is formed from the color intensity variations that can be seen as color texture of woven fabric. This study aims to find out among texture analysis using GLCM combined with color moment and texture analysis using CCM, which method gives better results for NTT woven fabric motif classification. The results showed that for NTT woven fabric motif classification, texture analysis using CCM gives better results, both on NMC and KNN classification method, with respectively 75% and 80%, than the combination of GLCM � color moment that give accuracy of 45% and 50%. With 640x480 pixels input image, CCM gives the trainning time 19 seconds and GLCM�color moment gives 11 seconds, while for the classification time CCM gives 378 milliseconds and GLCM�color moment gives 223 milliseconds.