• DocumentCode
    185673
  • Title

    An adaptive computational method for color contrast based salient region detection

  • Author

    Xin Xu ; Weiwei Wu

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2014
  • fDate
    18-19 Oct. 2014
  • Firstpage
    54
  • Lastpage
    58
  • Abstract
    An adaptive salient region detection method is proposed in this study, which combines LAB and RGB feature space and fused the color and contrast features. This algorithm first extracts the color feature of each image block in the LAB space and the contrast feature in the RGB space, and then fuses the color feature saliency map and the contrast feature saliency map using the principal component analysis (PCA) method which can effectively retain the saliency information of color and contrast, at last, this research extracts the salient region by setting a adaptive threshold. Compared with other detection methods, the proposed method is accurate and highlights the salient region uniformly, the detection results are more in line with the observations of human eyes.
  • Keywords
    adaptive signal processing; feature extraction; image colour analysis; image fusion; principal component analysis; LAB feature space; LAB space; PCA method; RGB feature space; RGB space; adaptive computational method; adaptive salient region detection method; adaptive threshold; color contrast; color feature extraction; color feature saliency map fusion; color fusion; contrast feature fusion; contrast feature saliency map; principal component analysis method; Color; Data mining; Decision support systems; Feature extraction; Fuses; Image color analysis; Principal component analysis; PCA fusion; color feature; contrast feature; salient region detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Security, Pattern Analysis, and Cybernetics (SPAC), 2014 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4799-5352-3
  • Type

    conf

  • DOI
    10.1109/SPAC.2014.6982656
  • Filename
    6982656