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Artikel Jurnal :: Kembali

Judul Query region determination based on region importance index and relative position for region-based image retrieval / Pasnur, Agus Zainal Arifin, Anny Yuniarti
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Pengarang
Pengarang/kontributor lain
Subjek
Penerbitan 2016
Kata Kunci Local binary pattern · Region-based image retrieval · Region importance index · Relative position · Region code · Saliency region ·
 Info Lainnya
ISSN20872100
Deskripsi Fisiknone
Catatan Umumnone
VolumeVol 7, No 4 (2016) 654-662
Akses Elektronik http://www.ijtech.eng.ui.ac.id/index.php/journal/article/view/1546
Institusi Pemilik Universitas Indonesia
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Nomor Panggil No. Barkod Ketersediaan
PDF 03-17-355520186 TERSEDIA
Ulasan:
Tidak ada ulasan pada koleksi ini: 20449844
An efficient
Region-Based Image Retrieval (RBIR) system must consider query region
determination techniques and target regions in the retrieval process. A query region is a region
that must contain
a Region of Interest (ROI) or saliency region. A query region determination can be specified
manually or automatically. However, manual determination is considered less
efficient and tedious for users. The selected query region must determine specific
target regions in the image collection to reduce the retrieval time. This study
proposes a strategy of query region determination based on the Region
Importance Index (RII) value and relative position of the Saliency Region
Overlapping Block (SROB) to produce a more efficient RBIR. The entire region is
formed by using the mean shift segmentation method. The RII value is calculated
based on a percentage of the region area and region distance to the center of
the image. Whereas
the target regions are determined by considering the relative position of SROB,
the performance of the proposed method is tested on a CorelDB dataset.
Experimental results show that the proposed method can reduce the Average of
Retrieval Time to 0.054 seconds with a 5x5 block size configuration.
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245|a Query region determination based on region importance index and relative position for region-based image retrieval / Pasnur, Agus Zainal Arifin, Anny Yuniarti |c
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520An efficient Region-Based Image Retrieval (RBIR) system must consider query region determination techniques and target regions in the retrieval process. A query region is a region that must contain a Region of Interest (ROI) or saliency region. A query region determination can be specified manually or automatically. However, manual determination is considered less efficient and tedious for users. The selected query region must determine specific target regions in the image collection to reduce the retrieval time. This study proposes a strategy of query region determination based on the Region Importance Index (RII) value and relative position of the Saliency Region Overlapping Block (SROB) to produce a more efficient RBIR. The entire region is formed by using the mean shift segmentation method. The RII value is calculated based on a percentage of the region area and region distance to the center of the image. Whereas the target regions are determined by considering the relative position of SROB, the performance of the proposed method is tested on a CorelDB dataset. Experimental results show that the proposed method can reduce the Average of Retrieval Time to 0.054 seconds with a 5x5 block size configuration.
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650Technology
653Local binary pattern; Region-based image retrieval; Region importance index; Relative position; Region code; Saliency region
700Agus Zainal Arifin, author Anny Yuniarti, author
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850Universitas Indonesia
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856http://www.ijtech.eng.ui.ac.id/index.php/journal/article/view/1546
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