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基于视觉词袋与文本分析的成人图像判定算法
引用本文:傅泉生,董开坤,尹璐.基于视觉词袋与文本分析的成人图像判定算法[J].计算机工程与应用,2015,51(4):175-179.
作者姓名:傅泉生  董开坤  尹璐
作者单位:哈尔滨工业大学(威海) 计算机科学与技术学院,山东 威海 264209
基金项目:山东省自然科学基金计划项目(No..ZR2012FM021)。
摘    要: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。

关 键 词:成人图像  图像识别  视觉词袋  文本分析  SVM分类  

Adult image recognition algorithm based on Bag-of-Visual-Words and text analysis
FU Quansheng,DONG Kaikun,YIN Lu.Adult image recognition algorithm based on Bag-of-Visual-Words and text analysis[J].Computer Engineering and Applications,2015,51(4):175-179.
Authors:FU Quansheng  DONG Kaikun  YIN Lu
Affiliation:School of Computer Science and Technology, Harbin Institute of Technology at Weihai, Weihai, Shandong 264209, China
Abstract: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.
Keywords:pornographic image  image recognition  Bag-of-Visual-Words  text analysis  SVM classification
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