计算机应用与软件
計算機應用與軟件
계산궤응용여연건
COMPUTER APPLICATIONS AND SOFTWARE
2013年
9期
263-265,295
,共4页
支持矢量机%模糊支持矢量机%层次语义%图像分类
支持矢量機%模糊支持矢量機%層次語義%圖像分類
지지시량궤%모호지지시량궤%층차어의%도상분류
SVM%FSVM%Hierarchical semantics%Image classification
为了解决层次语义图像中分类率低,特别是高层语义图像分类率低的问题,采用两种解决措施。首先引入Fuzzy Support Vector Machine ( FSVM)理论,并对FSVM做出改进,消除由Support Vector Machine ( SVM)构成的多类分类器中的不可分区域,从而使低层语义图像分类准确率提升,为高层语义分类提供基础。然后再建立底层图像特征与低层语义图像之间的映射关系,对低层语义的图像做高层语义上的关联,最终实现层次化的语义描述结构。实验表明,所提出的方法提高了层次语义图像,特别是高层语义图像分类准确率。
為瞭解決層次語義圖像中分類率低,特彆是高層語義圖像分類率低的問題,採用兩種解決措施。首先引入Fuzzy Support Vector Machine ( FSVM)理論,併對FSVM做齣改進,消除由Support Vector Machine ( SVM)構成的多類分類器中的不可分區域,從而使低層語義圖像分類準確率提升,為高層語義分類提供基礎。然後再建立底層圖像特徵與低層語義圖像之間的映射關繫,對低層語義的圖像做高層語義上的關聯,最終實現層次化的語義描述結構。實驗錶明,所提齣的方法提高瞭層次語義圖像,特彆是高層語義圖像分類準確率。
위료해결층차어의도상중분류솔저,특별시고층어의도상분류솔저적문제,채용량충해결조시。수선인입Fuzzy Support Vector Machine ( FSVM)이론,병대FSVM주출개진,소제유Support Vector Machine ( SVM)구성적다류분류기중적불가분구역,종이사저층어의도상분류준학솔제승,위고층어의분류제공기출。연후재건립저층도상특정여저층어의도상지간적영사관계,대저층어의적도상주고층어의상적관련,최종실현층차화적어의묘술결구。실험표명,소제출적방법제고료층차어의도상,특별시고층어의도상분류준학솔。
This paper uses two solutions for the problem of low classification rate in hierarchical semantic images , in particular the high-level hierarchical semantic images .Firstly we introduce the theory of fuzzy support vector machine ( FSVM ) and improve it , this eliminates the unclassifiable region of the multi-class classifiers constructed with support vector machine ( SVM ) , therefore the image classification accuracy rate of lower-level semantic images is enhanced;it provides a basis for the high-level semantic classification .Then, we establish the mapping relationship between the bottom image characteristics and the lower-level semantic images for making the association of high-level semantics for low-level semantic image , and finally achieve the hierarchical semantic description structure .Experimental results show that the presented method can improve the classification accuracy rate of hierarchical semantic images , especially of the high-level hierarchical semantic images .