View Item 
      •   Home
      • 1. Schools
      • College of Engineering
      • School of Computer Science and Engineering (SCSE)
      • SCSE Journal Articles
      • View Item
      •   Home
      • 1. Schools
      • College of Engineering
      • School of Computer Science and Engineering (SCSE)
      • SCSE Journal Articles
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.
      Subject Lookup

      Browse

      All of DR-NTUCommunities & CollectionsTitlesAuthorsBy DateSubjectsThis CollectionTitlesAuthorsBy DateSubjects

      My Account

      Login

      Statistics

      Most Popular ItemsStatistics by CountryMost Popular Authors

      About DR-NTU

      Weighted color and texture sample selection for image matting

      Thumbnail
      Author
      Varnousfaderani, Ehsan Shahrian
      Rajan, Deepu
      Date of Issue
      2013
      School
      School of Computer Engineering
      Research Centre
      Centre for Multimedia and Network Technology
      Abstract
      Color sampling based matting methods find the best known samples for foreground and background colors of unknown pixels. Such methods do not perform well if there is an overlap in the color distribution of foreground and background regions because color cannot distinguish between these regions and hence, the selected samples cannot reliably estimate the matte. Furthermore, current sampling based matting methods choose samples that are located around the boundaries of foreground and background regions. In this paper, we overcome these two problems. First, we propose texture as a feature that can complement color to improve matting by discriminating between known regions with similar colors. The contribution of texture and color is automatically estimated by analyzing the content of the image. Second, we combine local sampling with a global sampling scheme that prevents true foreground or background samples to be missed during the sample collection stage. An objective function containing color and texture components is optimized to choose the best foreground and background pair among a set of candidate pairs. Experiments are carried out on a benchmark data set and an independent evaluation of the results shows that the proposed method is ranked first among all other image matting methods.
      Subject
      DRNTU::Engineering::Computer science and engineering
      Type
      Journal Article
      Series/Journal Title
      IEEE transactions on image processing
      Collections
      • SCSE Journal Articles
      http://dx.doi.org/10.1109/TIP.2013.2271549
      Get published version (via Digital Object Identifier)

      Show full item record


      NTU Library, Nanyang Avenue, Singapore 639798 © 2011 Nanyang Technological University. All rights reserved.
      DSpace software copyright © 2002-2015  DuraSpace
      Contact Us | Send Feedback
      Share |    
      Theme by 
      Atmire NV
       

       


      NTU Library, Nanyang Avenue, Singapore 639798 © 2011 Nanyang Technological University. All rights reserved.
      DSpace software copyright © 2002-2015  DuraSpace
      Contact Us | Send Feedback
      Share |    
      Theme by 
      Atmire NV
       

       

      DCSIMG