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基于Curvelet-散射特征的圖像紋理分類
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國家自然科學(xué)基金資助項(xiàng)目(61162016,、60962004)


Image Texture Classification Based on Curvelet-Scattering Features
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    摘要:

    在二代曲線波的基礎(chǔ)上,提出一種旋轉(zhuǎn)不變曲波特征,然后結(jié)合具有平移不變性和Lipschitz 連續(xù)性的散射向量特征用于對紋理圖像的分類研究,。通過系統(tǒng)分析以及嚴(yán)格實(shí)驗(yàn)可以得出,,旋轉(zhuǎn)不變曲波紋理特征優(yōu)于廣泛使用的Gabor紋理特征,,且Curvelet-散射組合特征在紋理分類上具有很高準(zhǔn)確率以及計(jì)算紋理特征的效率,,和單一的散射特征相比,,具有一定的優(yōu)勢,。

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    A Curvelet feature with rotation invariant was put forward on the basis of the theory of the second generation Curvelet, and used for classification of texture images combination with the scattering feature vectors which have translation invariance and Lipschitz succession. With systematic analysis and rigorous experiments, the proposed Curvelet features significantly outperforms the widely used Gabor texture features. The combination features of Curvelet-scattering had high accuracy and computation efficiency for texture classification, and had a certain advantages compared with the single scattering features. 

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馮鑫,王曉明,黨建武.基于Curvelet-散射特征的圖像紋理分類[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2012,43(10):184-189,199. Feng Xin,Wang Xiaoming, Dang Jianwu. Image Texture Classification Based on Curvelet-Scattering Features[J]. Transactions of the Chinese Society for Agricultural Machinery,2012,43(10):184-189,199.

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  • 在線發(fā)布日期: 2012-10-19
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