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	Multi-scale Joint Encoding of Local Binary Patterns for Texture and Material Classification
	Xianbiao Qi; Yu Qiao; Chun-Guang Li; Jun Guo
	2013
会议名称	2013 24th British Machine Vision Conference, BMVC 2013
会议地点	Bristol, United kingdom
英文摘要	In the current multi-scale LBP (MS-LBP) on texture and material classification, each scale is encoded into histograms individually. This strategy ignores the correlation between different scales, and loses a lot of discriminative information. In this paper, we propose a novel and effective multi-scale joint encoding oflocal binary patterns (MSJ-LBP) for texture and material classification. In MSJ-LBP, the joint encoding strategy can capture the correlation between different scales and hence depict richer local structures. In addition, the proposed MSJ-LBP is computationally simple and rotation invariant. Extensive experiments on four challenging databases (Outex_TC_00012, Brodatz, KTH-TIPS, KTH-TIPS2a) show that the proposed MSJ-LBP significantly outperforms the classical MS-LBP and achieves the state-of-the-art performance.
收录类别	EI
语种	中文
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/4486]
专题	深圳先进技术研究院_集成所
作者单位	2013
推荐引用方式 GB/T 7714	Xianbiao Qi,Yu Qiao,Chun-Guang Li,et al. Multi-scale Joint Encoding of Local Binary Patterns for Texture and Material Classification[C]. 见:2013 24th British Machine Vision Conference, BMVC 2013. Bristol, United kingdom.

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