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Non-subsampled contourlets and gray level co-occurrence matrix based images segmentation

Authors: Zhang Jian; Chen Xiaowei;

Non-subsampled contourlets and gray level co-occurrence matrix based images segmentation

Abstract

Contourlet is a new geometric multiscale tool that is based on multiscale filters and directional filter banks. It not only inherits the multiscale characteristics of dimensionality-inseparable wavelets, but also has the flexible multi-directional characteristic by changing the directions of transform and sequences. In this paper, we developed a new non-subsampled contourlet transform (NSCT) and gray level co-occurrence matrix (GLCM) based image segmentation method. For the redundant and shift-invariant property of the NSCT, and the statistical texture features extracted by GLCM, the proposed method can present accurate segmentation result.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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