A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGION

One of the techniques in region based image retrieval (RBIR) is comparing the global feature of an entire image and the local feature of image’s sub-block in query and database image. The determined sub-block must be able to detect an object with varying sizes and locations. So the sub-block with fl...

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Main Authors: Ahmad Wahyu Rosyadi, Renest Danardono, Siprianus Septian Manek, Agus Zainal Arifin
Format: Article
Language:English
Published: Universitas Indonesia 2018-02-01
Series:Jurnal Ilmu Komputer dan Informasi
Subjects:
HSV
LBP
Online Access:http://jiki.cs.ui.ac.id/index.php/jiki/article/view/471
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spelling doaj-b24e03a6733e4de3bb516a5fb7373ae22020-11-25T00:55:59ZengUniversitas IndonesiaJurnal Ilmu Komputer dan Informasi2088-70512502-92742018-02-01111425110.21609/jiki.v11i1.471237A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGIONAhmad Wahyu Rosyadi0Renest Danardono1Siprianus Septian Manek2Agus Zainal Arifin3Institut Teknologi Sepuluh NopemberInstitut Teknologi Sepuluh NopemberInstitut Teknologi Sepuluh NopemberInstitut Teknologi Sepuluh NopemberOne of the techniques in region based image retrieval (RBIR) is comparing the global feature of an entire image and the local feature of image’s sub-block in query and database image. The determined sub-block must be able to detect an object with varying sizes and locations. So the sub-block with flexible size and location is needed. We propose a new method for local feature extraction by determining the flexible size and location of sub-block based on the transition region in region based image retrieval. Global features of both query and database image are extracted using invariant moment. Local features in database and query image are extracted using hue, saturation, and value (HSV) histogram and local binary patterns (LBP). There are several steps to extract the local feature of sub-block in the query image. First, preprocessing is conducted to get the transition region, then the flexible sub-block is determined based on the transition region. Afterward, the local feature of sub-block is extracted. The result of this application is the retrieved images ordered by the most similar to the query image. The local feature extraction with the proposed method is effective for image retrieval with precision and recall value are 57%.http://jiki.cs.ui.ac.id/index.php/jiki/article/view/471RBIRTransition RegionInvariant momentHSVLBP
collection DOAJ
language English
format Article
sources DOAJ
author Ahmad Wahyu Rosyadi
Renest Danardono
Siprianus Septian Manek
Agus Zainal Arifin
spellingShingle Ahmad Wahyu Rosyadi
Renest Danardono
Siprianus Septian Manek
Agus Zainal Arifin
A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGION
Jurnal Ilmu Komputer dan Informasi
RBIR
Transition Region
Invariant moment
HSV
LBP
author_facet Ahmad Wahyu Rosyadi
Renest Danardono
Siprianus Septian Manek
Agus Zainal Arifin
author_sort Ahmad Wahyu Rosyadi
title A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGION
title_short A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGION
title_full A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGION
title_fullStr A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGION
title_full_unstemmed A FLEXIBLE SUB-BLOCK IN REGION BASED IMAGE RETRIEVAL BASED ON TRANSITION REGION
title_sort flexible sub-block in region based image retrieval based on transition region
publisher Universitas Indonesia
series Jurnal Ilmu Komputer dan Informasi
issn 2088-7051
2502-9274
publishDate 2018-02-01
description One of the techniques in region based image retrieval (RBIR) is comparing the global feature of an entire image and the local feature of image’s sub-block in query and database image. The determined sub-block must be able to detect an object with varying sizes and locations. So the sub-block with flexible size and location is needed. We propose a new method for local feature extraction by determining the flexible size and location of sub-block based on the transition region in region based image retrieval. Global features of both query and database image are extracted using invariant moment. Local features in database and query image are extracted using hue, saturation, and value (HSV) histogram and local binary patterns (LBP). There are several steps to extract the local feature of sub-block in the query image. First, preprocessing is conducted to get the transition region, then the flexible sub-block is determined based on the transition region. Afterward, the local feature of sub-block is extracted. The result of this application is the retrieved images ordered by the most similar to the query image. The local feature extraction with the proposed method is effective for image retrieval with precision and recall value are 57%.
topic RBIR
Transition Region
Invariant moment
HSV
LBP
url http://jiki.cs.ui.ac.id/index.php/jiki/article/view/471
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