ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN (STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR)
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 fab...
| Main Authors: | , |
|---|---|
| Format: | Thesis |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2013
|
| Subjects: |
| _version_ | 1826047533746487296 |
|---|---|
| author | , Nicodemus Mardanus Setiohardjo , Drs. Agus Harjoko, M.Sc, Ph.D |
| author_facet | , Nicodemus Mardanus Setiohardjo , Drs. Agus Harjoko, M.Sc, Ph.D |
| author_sort | , Nicodemus Mardanus Setiohardjo |
| collection | UGM |
| description | 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. |
| first_indexed | 2024-03-13T23:12:21Z |
| format | Thesis |
| id | oai:generic.eprints.org:125977 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:12:21Z |
| publishDate | 2013 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1259772016-03-04T08:41:26Z https://repository.ugm.ac.id/125977/ ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN (STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR) , Nicodemus Mardanus Setiohardjo , Drs. Agus Harjoko, M.Sc, Ph.D ETD 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. [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , Nicodemus Mardanus Setiohardjo and , Drs. Agus Harjoko, M.Sc, Ph.D (2013) ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN (STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR). UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=66159 |
| spellingShingle | ETD , Nicodemus Mardanus Setiohardjo , Drs. Agus Harjoko, M.Sc, Ph.D ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN (STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR) |
| title | ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN
(STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR) |
| title_full | ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN
(STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR) |
| title_fullStr | ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN
(STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR) |
| title_full_unstemmed | ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN
(STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR) |
| title_short | ANALISIS TEKSTUR UNTUK KLASIFIKASI MOTIF KAIN
(STUDI KASUS KAIN TENUN NUSA TENGGARA TIMUR) |
| title_sort | analisis tekstur untuk klasifikasi motif kain studi kasus kain tenun nusa tenggara timur |
| topic | ETD |
| work_keys_str_mv | AT nicodemusmardanussetiohardjo analisisteksturuntukklasifikasimotifkainstudikasuskaintenunnusatenggaratimur AT drsagusharjokomscphd analisisteksturuntukklasifikasimotifkainstudikasuskaintenunnusatenggaratimur |