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".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Esta carta propõe um novo tipo de recursos para recuperação de imagens coloridas com base em histogramas de índice de quantização vetorial preditiva de limite ponderado por distância (DWBPVQ). Para cada imagem colorida no banco de dados, 6 histogramas (2 para cada componente de cor) são calculados a partir das seis sequências de índice DWBPVQ correspondentes. Os resultados da simulação de recuperação mostram que, em comparação com os recursos tradicionais baseados em histograma de cores de domínio espacial (SCH) e os recursos baseados em histograma de índice DCTVQ (DCTVQIH), os recursos DWBPVQIH propostos podem melhorar muito o desempenho de recuperação e precisão.
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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},}
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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 -