Statistical multiscale blob features for classifying and retrieving image texture from large-scale databases
Statistical multiscale blob features for classifying and retrieving image texture from large-scale databases
复制标题
用于从大型数据库中分类和检索图像纹理的统计多尺度 blob 特征
DOI:
10.1117/1.3491420
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发表时间:
2010-10
影响因子:
1.1
通讯作者:
Wu, Haishan
中科院分区:
文献类型:
--
作者:
Chen, Yan Qiu;Xu, Qi;Wu, Haishan
The extraction of texture features from images faces two new challenges: large-scale databases with diversified textures, and varying imaging conditions. We propose a novel method termed multiscale blob features (MBF) to overcome these two difficulties. MBF analyzes textures in both resolution scale and gray level. Proposed statistical descriptors effectively extract structural information from the decomposed binary images. Experimental results show that MBF outperforms other methods on combined large-scale databases (VisTex+Brodatz+CUReT+OuTex). Moreover, experimental results on the University of Illinois at Urbana-Champaign database and the entire Brodatz's atlas show that MBF is invariant to gray-level scaling and image rotation, and is robust across a substantial range of spatial scaling.
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DOI:
10.1109/tpami.2005.151
发表时间:
2005-08-01
影响因子:
23.6
作者:
Lazebnik, S;Schmid, C;Ponce, J
通讯作者:
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1992-03
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影响因子:
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影响因子:
6.2
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期刊:
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通讯作者:
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DOI:
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发表时间:
1992-03
期刊:
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影响因子:
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作者:
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G. Salton