• DocumentCode
    723320
  • Title

    DeWAFF: A novel image abstraction approach to improve the performance of a cell tracking system

  • Author

    Calderon, S. ; Saenz, A. ; Mora, R. ; Siles, F. ; Orozco, I. ; Buemi, M.E.

  • Author_Institution
    Dept. of Electr. Eng., Univ. de Costa Rica, San Jose, Costa Rica
  • fYear
    2015
  • fDate
    10-12 June 2015
  • Firstpage
    81
  • Lastpage
    88
  • Abstract
    This paper presents a new image abstraction approach, aiming to improve typical image related pattern recognition tasks such as segmentation, tracking, and classification. The proposed image abstraction framework performs image denoising and homogeneous region simplification, along with border and region enhancement. The proposed framework consists in a novel generalized approach of common weighted averaging denoising algorithms mixed with Unsharp Masking (USM) border enhancement techniques, to avoid typical USM artifacts as ringing. Results of the different configurations within the image abstraction framework for a cell tracking application are presented.
  • Keywords
    biology computing; cellular biophysics; image classification; image denoising; image enhancement; image segmentation; DeWAFF; USM artifacts; cell tracking system; common weighted averaging denoising algorithms; homogeneous region simplification; image abstraction approach; image classification; image denoising; image related pattern recognition tasks; image segmentation; image tracking; region enhancement; unsharp masking border enhancement techniques; AWGN; Histograms; Image edge detection; Image segmentation; Noise reduction; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinspired Intelligence (IWOBI), 2015 4th International Work Conference on
  • Conference_Location
    San Sebastian
  • Print_ISBN
    978-1-4673-7845-1
  • Type

    conf

  • DOI
    10.1109/IWOBI.2015.7160148
  • Filename
    7160148