• DocumentCode
    1808131
  • Title

    A Study on the Algorithm Based on Image Color Correlation Mining

  • Author

    Chen YongYue ; Xia Huosong

  • Author_Institution
    Dept. of Inf. Manage. & Inf. Syst., Wuhan Univ. of Sci. & Eng., Wuhan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    18-20 Aug. 2009
  • Firstpage
    377
  • Lastpage
    380
  • Abstract
    Because of the semantic gap between low-level feature and high-level semantic feature of images, the results of the traditional color-based image retrieval canpsilat meet userspsila needs. In order to eliminate interference factors in the image retrieval, use image semantic feature and improve the accuracy of image retrieval, the paper introduces an algorithm based on the color correlation mining. It regards the pixel rows as a transaction set, uses the Apriori algorithm to find out the rows by looking for the continual co-occurrence color in the transaction set. These rows are correlative with the semantic object of the image. Then it extracts the correlative color histogram of image form the correlative color set to realize the correlative color mining.
  • Keywords
    correlation methods; data mining; feature extraction; image colour analysis; image retrieval; statistical analysis; Apriori algorithm; continual co-occurrence color; feature extraction; high-level semantic feature; histogram; image color correlation mining; image retrieval; interference factor elimination; low-level semantic feature; pixel row; semantic gap; transaction set; Data mining; Feature extraction; Histograms; Image retrieval; Information management; Information retrieval; Information security; Management information systems; Pixel; Quantization; Apriori algorithm; correlative color mining; image retrieve;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
  • Conference_Location
    Xian
  • Print_ISBN
    978-0-7695-3744-3
  • Type

    conf

  • DOI
    10.1109/IAS.2009.143
  • Filename
    5283440