• DocumentCode
    1797028
  • Title

    Automatic region of interest extraction in food baking images

  • Author

    Jiannan Zheng ; Wang, Z. Jane ; Ziraknejad, Nima ; Saxena, Pratiksha

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
  • fYear
    2014
  • fDate
    9-13 July 2014
  • Firstpage
    291
  • Lastpage
    295
  • Abstract
    This paper presents a novel approach to automatically detect the region of interest (ROI) in food baking images. In addition to common ROI extraction and saliency extraction problems, food baking images are also subject to lighting noise, glass reflection and shadow effects. In this paper, the HSV color map is employed to effectively eliminate oven lighting effects, then a one-bit transform (1BT) with global adaptive thresholding method is performed to obtain preliminary ROI segmentation results. Further, a local contour refinement algorithm is designed to reduce glass reflection and shadow effects for extracting the ROI contour more precisely. The ROI extraction results presented in this paper can be used in compression and transmission of food baking images and videos for further analysis.
  • Keywords
    bakeries; data compression; feature extraction; food technology; image colour analysis; image denoising; image segmentation; transforms; video coding; video communication; 1BT; HSV color map; automatic region of interest extraction; food baking image transmission; food baking images compression; glass reflection reduction; global adaptive thresholding method; lighting noise; local contour refinement algorithm; one-bit transform; preliminary ROI segmentation; saliency extraction problem; shadow effect; video compression; video transmission; Colored noise; Glass; Image color analysis; Image segmentation; Ovens; Reflection; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (ChinaSIP), 2014 IEEE China Summit & International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4799-5401-8
  • Type

    conf

  • DOI
    10.1109/ChinaSIP.2014.6889250
  • Filename
    6889250