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Image Retrieval Based on Multi Structure Co-occurrence Descriptor

Journal from gdlhub / 2016-11-09 04:03:58
Oleh : Agus Eko Minarno, Arrie Kurniawardhani, Fitri Bimantoro, Telkomnika
Dibuat : 2016-09-01, dengan 1 file

Keyword : Batik, Image retrieval, Micro Structure, Gray Level Co-occurrence Matrix
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/3292

This study present a new technique for Batik cloth image retrieval using Micro-Structure Co-occurence Descriptor (MSCD). MSCD is a developed method based on Enhanced Micro Structure Descriptor (EMSD). Previously, EMSD has been improved by adding edge orientation feature. In previous study, EMSD cannot achieve an optimal precision. Therefore, MSCD is proposed to overcome the EMSD drawback using global feature approach, namely Gray Level Co-occurrence Matrix (GLCM). There are 300 batik cloth images which contain 50 classes used for dataset. The performance result show that MSCD can retrieve Batik cloth images more effective than EMSD

Deskripsi Alternatif :

This study present a new technique for Batik cloth image retrieval using Micro-Structure Co-occurence Descriptor (MSCD). MSCD is a developed method based on Enhanced Micro Structure Descriptor (EMSD). Previously, EMSD has been improved by adding edge orientation feature. In previous study, EMSD cannot achieve an optimal precision. Therefore, MSCD is proposed to overcome the EMSD drawback using global feature approach, namely Gray Level Co-occurrence Matrix (GLCM). There are 300 batik cloth images which contain 50 classes used for dataset. The performance result show that MSCD can retrieve Batik cloth images more effective than EMSD

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