• DocumentCode
    3467242
  • Title

    Insect Soup Challenge: Segmentation, Counting, and Simple Classification

  • Author

    Mele, Katarina

  • Author_Institution
    Riverside Life Sci. Centre, North Ryde, NSW, Australia
  • fYear
    2013
  • fDate
    2-8 Dec. 2013
  • Firstpage
    168
  • Lastpage
    171
  • Abstract
    In the paper we present a method for segmentation of insects from the Insect Soup images. The method enables reliable segmentation of insects of variable size, shape and color. After segmentation, a set of properties are assigned to each segmented insect which enables classification into different categories. The approach was successfully applied on two different types of real life images: images from the Insect Soup Challenge and images acquired from traps in the field using low resolution cameras.
  • Keywords
    cameras; image classification; image resolution; image segmentation; image acquisition; insect classification; insect counting; insect segmentation; insect soup challenge; insect soup images; insects segmentation; low resolution cameras; real life images; Extremities; Image color analysis; Image resolution; Image segmentation; Insects; Noise; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/ICCVW.2013.28
  • Filename
    6755893
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3467242