CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
Texture segmentation using directional empirical mode decomposition
Liu Zhongxuan; Wang Hongjian; Peng Silong; Zhongxuan Liu
2004
Conference Name2004 International Conference on Image Processing ICIP 2004
Pagespp 279-282
Conference Date2004/10/24-2004/10/27
Conference PlaceSingaporeSingapore
AbstractIn this paper the technique of Directional Empirical Mode Decomposition (DEMD) and ils application to texture segmentation are presented. Empirical Mode Decomposition (EMD) decomposessignals by sifting and then analyzes the instantaneous frequency of the obtained components called Intrinsic Mode Functions (IMFs). As a new form of extending 1-D EMD to 2-D case DEMD considers the directional frequency and envelope at each point. One type of 2-D Hilbert transform is introduced to compute the analytical functions for the frequency and envelope. The technique of selecting directions for DEMD based on texture’s Wold theory is also presented. Experimental results indicate the effectiveness of the method for texture segmentation.
Keyword
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12897
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorZhongxuan Liu
Recommended Citation
GB/T 7714
Liu Zhongxuan,Wang Hongjian,Peng Silong,et al. Texture segmentation using directional empirical mode decomposition[C],2004:pp 279-282.
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