CAJ | 학술논문

针对目前单纯依赖于分析图像内容或文本关键词的成人图像判定算法的不足，提出一种融合网络图像的相关文本特征与图像内容语义特征的成人图像判定算法。成人图像的特征信息可能存在于其图像内容及其相关文本如图像文件名、所在网页中。在视觉词袋模型的基础上，将文本分析得到的相关文本特征与图像视觉元素特征如纹理、局部形态等进行底层特征融合，并采用支持向量机分类器实现图像分类。实验结果表明，该算法具有较好的分类效果。
침대목전단순의뢰우분석도상내용혹문본관건사적성인도상판정산법적불족，제출일충융합망락도상적상관문본특정여도상내용어의특정적성인도상판정산법。성인도상적특정신식가능존재우기도상내용급기상관문본여도상문건명、소재망혈중。재시각사대모형적기출상，장문본분석득도적상관문본특정여도상시각원소특정여문리、국부형태등진행저층특정융합，병채용지지향량궤분류기실현도상분류。실험결과표명，해산법구유교호적분류효과。
In view of the disadvantage of the present adult image recognition algorithms such as ones only depend on the image content or keywords of text, this paper proposes a new adult web images recognition algorithm fusing the features of relative text and image semantic. Adult image feature information may exist in its image content and its associated text, such as the image file name or the webpage. Based on Bag-of-Visual-Words model, this algorithm coalesce text features extracted by analysis of corresponding text and visual features by analysis of image content such as texture, local shape on the low-level, and accomplishes image classification by using SVM classifier. The experimental results demonstrate effective classification capability of this algorithm.