本文選題：煙花算法 + 軟子空間聚類��； 參考：《軟件學(xué)報(bào)》2017年11期

【摘要】：現(xiàn)有的軟子空間聚類算法在分割MR圖像時(shí)易受隨機(jī)噪聲的影響,而且算法因依賴于初始聚類中心的選擇而容易陷入局部最優(yōu),導(dǎo)致分割效果不理想.針對(duì)這一問(wèn)題,提出一種基于煙花算法的軟子空間MR圖像聚類算法.算法首先設(shè)計(jì)一個(gè)結(jié)合界約束與噪聲聚類的目標(biāo)函數(shù),彌補(bǔ)現(xiàn)有算法對(duì)噪聲數(shù)據(jù)敏感的缺陷,并提出一種隸屬度計(jì)算方法,快速、準(zhǔn)確地尋找簇類所在子空間;然后,在聚類過(guò)程中引入自適應(yīng)煙花算法,有效地平衡局部與全局搜索,彌補(bǔ)現(xiàn)有算法容易陷入局部最優(yōu)的不足.EWKM,FWKM,FSC,LAC算法在UCI數(shù)據(jù)集、人工合成圖像、Berkeley圖像數(shù)據(jù)集以及臨床乳腺M(fèi)R圖像、腦部MR圖像上的聚類結(jié)果表明,所提出的算法不僅在UCI數(shù)據(jù)集上能夠取得較好的結(jié)果,而且對(duì)圖像聚類也具有較好的抗噪性能,尤其是對(duì)MR圖像的聚類具有較高的精度和魯棒性,能夠較為有效地實(shí)現(xiàn)MR圖像的分割.
[Abstract]:The existing soft subspace clustering algorithms are susceptible to random noise in the segmentation of Mr images, and the algorithm is prone to fall into local optimum because of its dependence on the selection of initial clustering centers, which leads to unsatisfactory segmentation results.To solve this problem, a soft subspace Mr image clustering algorithm based on fireworks algorithm is proposed.The algorithm first designs an objective function combining bound constraints and noise clustering to make up for the shortcomings of the existing algorithms which are sensitive to noise data, and proposes a method for calculating membership degree, which can quickly and accurately find the subspace where the cluster is located.In the process of clustering, adaptive fireworks algorithm is introduced to balance the local and global search effectively, to make up for the deficiency of the existing algorithms. EWKM / FWKMU / FSCSC-LAC algorithm is applied to UCI data sets, artificial synthetic images, Berkeley image datasets and clinical mammary Mr images.The clustering results on brain Mr images show that the proposed algorithm can not only obtain better results on UCI datasets, but also have a good anti-noise performance for image clustering.Especially, it has high accuracy and robustness to the clustering of Mr images, and it can effectively realize the segmentation of Mr images.
【作者單位】： 陜西師范大學(xué)計(jì)算機(jī)科學(xué)學(xué)院;中國(guó)科學(xué)院深圳先進(jìn)技術(shù)研究院生物醫(yī)學(xué)與健康工程研究所;
【分類號(hào)】：TP18;TP391.41

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