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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Universitas Indonesia
2018-02-01
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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 |
work_keys_str_mv |
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