计算机应用 ›› 2017, Vol. 37 ›› Issue (11): 3238-3243.DOI: 10.11772/j.issn.1001-9081.2017.11.3238

• 2017年中国计算机学会人工智能会议(CCFAI 2017) • 上一篇    下一篇

基于颜色的压缩层次图像表示方法

朱杰1, 吴树芳2,3, 谢博鋆4, 马丽艳5   

  1. 1. 中央司法警官学院 信息管理系, 河北 保定 071000;
    2. 天津大学 管理与经济学部, 天津 300072;
    3. 河北大学 管理学院, 河北 保定 071000;
    4. 河北大学 数学与信息科学学院, 河北 保定 071000;
    5. 中国科学院 微电子研究所, 北京 100029
  • 收稿日期:2017-05-11 修回日期:2017-06-05 出版日期:2017-11-10 发布日期:2017-11-11
  • 通讯作者: 吴树芳
  • 作者简介:朱杰(1982-),男,河北保定人,副教授,博士,主要研究方向:机器学习、计算机视觉;吴树芳(1980-),女,河北邯郸人,副教授,博士,主要研究方向:信息检索、机器学习;谢博鋆(1981-),男,河北保定人,讲师,博士,主要研究方向:机器学习、计算机视觉;马丽艳(1983-),女,北京人,助理研究员,博士,主要研究方向:计算机视觉。
  • 基金资助:
    国家自然科学基金资助项目(61402462);国家社会科学基金资助项目(17BTQ068);河北省教育厅青年基金资助项目(QN2015099);中央司法警官学院校级科研项目(XYZ201602);教育部人文社会科学研究青年基金资助项目(15YJC630021);河北省自然科学基金青年科学基金资助项目(F2018511002);河北大学中西部提升综合实力专项资金资助项目。

Color based compact hierarchical image representation

ZHU Jie1, WU Shufang2,3, XIE Bojun4, MA Liyan5   

  1. 1. Department of Information Management, the National Police University for Criminal Justice, Baoding Hebei 071000, China;
    2. College of Management and Economics, Tianjin University, Tianjin 300072, China;
    3. College of Management, Hebei University, Baoding Hebei 071000, China;
    4. College of Mathematics and Information Science, Hebei University, Baoding Hebei 071000, China;
    5. Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China
  • Received:2017-05-11 Revised:2017-06-05 Online:2017-11-10 Published:2017-11-11
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61402462), the National Social Science Foundation of China (17BTQ068), the Youth Foundation of Education Bureau of Hebei Province (QN2015099), the Research Program of the National Police University for Criminal Justice (XYZ201602), the Touth Foundation Project of Humanities and Social Sciences Research of Ministry of Education (15YJC630021), the Youth Foundation Project of Hebei Natural Science Foundation of China(F2018511002), the Special Funds to Enhance Central and Western Strength of Hebei University.

摘要: 空间金字塔模型在每层中把图像划分成细胞单元用于给图像表示提供空间信息,但是这种方式不能很好地匹配对象上的不同部分,为此提出一种基于颜色的层次(CL)划分算法。CL算法从多特征融合的角度出发,通过优化的方式在不同层次中得到每个类别中有判别力的颜色,然后根据每层中有判别力的颜色对图像进行迭代的层次划分;最后连接不同层次直方图用于图像表示。为了解决图像表示维度过高的问题,采用分化信息理论的特征聚类(DITC)方法对字典进行聚类用于字典降维,并用压缩生成的字典进行最终的图像表示。实验结果表明,所提方法能够在Soccer,Flower 17和Flower 102上取得良好的识别效果。

关键词: 有判别力的颜色, 层次, 维度约减, 分化信息理论的特征聚类, 对象识别

Abstract: The spatial pyramid matching method provides the spatial information by splitting an image into different cells. However, spatial pyramid matching can not match different parts of the objects well. A hierarchical image representation method based on Color Level (CL) was proposed. The class-specific discriminative colors of different levels were obtained from the viewpoint of feature fusion in CL algorithm, and then an image was iteratively split into different levels based on these discriminative colors. Finally, image representation was constructed by concatenating the histograms of different levels. To reduce the dimensionality of image representation, the Divisive Information-Theoretic feature Clustering (DITC) method was used to cluster the dictionary, and the generated compact dictionary was used for final image representation. Classification results on Soccer, Flower 17 and Flower 102 datasets, demonstrate that the proposed method can obtain satisfactory results in these datasets.

Key words: discriminative color, hierarchy, dimensional reduction, Divisive Information-Theoretic feature Clustering (DITC), object recognition

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