• DocumentCode
    3604933
  • Title

    Visual Quality Evaluation of Image Object Segmentation: Subjective Assessment and Objective Measure

  • Author

    Ran Shi ; King Ngi Ngan ; Songnan Li ; Paramesran, Raveendran ; Hongliang Li

  • Author_Institution
    Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Hong Kong, China
  • Volume
    24
  • Issue
    12
  • fYear
    2015
  • Firstpage
    5033
  • Lastpage
    5045
  • Abstract
    A visual quality evaluation of image object segmentation as one member of the visual quality evaluation family has been studied over the years. Researchers aim at developing the objective measures that can evaluate the visual quality of object segmentation results in agreement with human quality judgments. It is also significant to construct a platform for evaluating the performance of the objective measures in order to analyze their pros and cons. In this paper, first, we present a novel subjective object segmentation visual quality database, in which a total of 255 segmentation results were evaluated by more than thirty human subjects. Then, we propose a novel full-reference objective measure for an object segmentation visual quality evaluation, which involves four human visual properties. Finally, our measure is compared with some state-of-the-art objective measures on our database. The experiment demonstrates that the proposed measure performs better in matching subjective judgments. Moreover, the database is available publicly for other researchers in the field to evaluate their measures.
  • Keywords
    image segmentation; image object segmentation; objective measure; subjective assessment; subjective object segmentation visual quality database; visual quality evaluation; Distortion measurement; Image segmentation; Object segmentation; Semantics; Visual databases; Visualization; Object Segmentation; Object segmentation; Objective Measure; Subjective Evaluation; Visual Quality; objective measure; subjective evaluation; visual quality;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2015.2473099
  • Filename
    7222418