The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
이 편지는 거리 가중 경계 예측 벡터 양자화(DWBPVQ) 지수 히스토그램을 기반으로 컬러 이미지 검색을 위한 새로운 종류의 기능을 제안합니다. 데이터베이스의 각 컬러 이미지에 대해 6개의 히스토그램(각 컬러 구성요소당 2개)이 XNUMX개의 해당 DWBPVQ 인덱스 시퀀스에서 계산됩니다. 검색 시뮬레이션 결과는 기존의 공간 영역 색상 히스토그램 기반(SCH) 기능 및 DCTVQ 인덱스 히스토그램 기반(DCTVQIH) 기능과 비교하여 제안된 DWBPVQIH 기능이 재현율 및 정밀도 성능을 크게 향상시킬 수 있음을 보여줍니다.
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Zhen SUN, Zhe-Ming LU, Hao LUO, "Color Image Retrieval Based on Distance-Weighted Boundary Predictive Vector Quantization Index Histograms" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 9, pp. 1803-1806, September 2009, doi: 10.1587/transinf.E92.D.1803.
Abstract: This Letter proposes a new kind of features for color image retrieval based on Distance-weighted Boundary Predictive Vector Quantization (DWBPVQ) Index Histograms. For each color image in the database, 6 histograms (2 for each color component) are calculated from the six corresponding DWBPVQ index sequences. The retrieval simulation results show that, compared with the traditional Spatial-domain Color-Histogram-based (SCH) features and the DCTVQ index histogram-based (DCTVQIH) features, the proposed DWBPVQIH features can greatly improve the recall and precision performance.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1803/_p
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@ARTICLE{e92-d_9_1803,
author={Zhen SUN, Zhe-Ming LU, Hao LUO, },
journal={IEICE TRANSACTIONS on Information},
title={Color Image Retrieval Based on Distance-Weighted Boundary Predictive Vector Quantization Index Histograms},
year={2009},
volume={E92-D},
number={9},
pages={1803-1806},
abstract={This Letter proposes a new kind of features for color image retrieval based on Distance-weighted Boundary Predictive Vector Quantization (DWBPVQ) Index Histograms. For each color image in the database, 6 histograms (2 for each color component) are calculated from the six corresponding DWBPVQ index sequences. The retrieval simulation results show that, compared with the traditional Spatial-domain Color-Histogram-based (SCH) features and the DCTVQ index histogram-based (DCTVQIH) features, the proposed DWBPVQIH features can greatly improve the recall and precision performance.},
keywords={},
doi={10.1587/transinf.E92.D.1803},
ISSN={1745-1361},
month={September},}
부
TY - JOUR
TI - Color Image Retrieval Based on Distance-Weighted Boundary Predictive Vector Quantization Index Histograms
T2 - IEICE TRANSACTIONS on Information
SP - 1803
EP - 1806
AU - Zhen SUN
AU - Zhe-Ming LU
AU - Hao LUO
PY - 2009
DO - 10.1587/transinf.E92.D.1803
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2009
AB - This Letter proposes a new kind of features for color image retrieval based on Distance-weighted Boundary Predictive Vector Quantization (DWBPVQ) Index Histograms. For each color image in the database, 6 histograms (2 for each color component) are calculated from the six corresponding DWBPVQ index sequences. The retrieval simulation results show that, compared with the traditional Spatial-domain Color-Histogram-based (SCH) features and the DCTVQ index histogram-based (DCTVQIH) features, the proposed DWBPVQIH features can greatly improve the recall and precision performance.
ER -