Image Segmentation Using Hidden Markov Tree Methods in Recognizing of Batik

Murinto, Murinto and Aribowo, Eko (2016) Image Segmentation Using Hidden Markov Tree Methods in Recognizing of Batik. [Artikel Dosen]

Text HASIL CEK_Murinto_IMAGE SEGMENTATION USING HIDDEN MARKOV TREE METHODS IN RECOGNIZING MOTIF OF BATIK.pdf Download (2MB)

Abstract

Batik is one of the inherited high-valued artwork. Batik is a way of making clothes using fabric coloring
technique. This technique uses ‘malam’ to avoid staining unintended parts of the fabric. The term ‘Batik’
can also be referred to a cloth that is made with coloring technique, possesses certain motifs as well as
special characteristic. Batik’s motif pattern recognition requires initial image processing step called as
image segmentation. The purpose of image segmentation is to divide the image into several regions based on feature similarity including grayscale level, texture, color, and motion. In this research multiscale segmentation methods, HMTSeg, is used to recognize the pattern of batik’s motif. Images of Batik that have been used in this work are images of Batik originated from Jambi region, Pekalongan region, and Yogyakarta region. Batik’s motif pattern recognition steps include image pre-processing, image segmentation, and pattern recognition using Euclidean distance based method. Result shows that this method gained 80% of accuracy in recognizing batik’s motif. In conclusion, HMTSeg is a good segmentation method to recognize pattern of batik based on the texture

Item Type:	Artikel Dosen
Subjects:	T Technology > T Technology (General)
Divisi / Prodi:	Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Informatics Engineering (S1-Teknik Informatika)
Depositing User:	murinto murinto
Date Deposited:	22 Sep 2023 02:10
Last Modified:	23 Sep 2023 05:52
URI:	http://eprints.uad.ac.id/id/eprint/50444

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