• DocumentCode
    2805617
  • Title

    Detecting the excessive activation of the ciliaris muscle on thermal images

  • Author

    Harangi, B. ; Csordás, T. ; Hajdu, A.

  • Author_Institution
    Fac. of Inf., Univ. of Debrecen, Debrecen, Hungary
  • fYear
    2011
  • fDate
    27-29 Jan. 2011
  • Firstpage
    329
  • Lastpage
    331
  • Abstract
    In this paper, we present our newest results from special field of thermal image processing. We study the behaviour of muscle of human eye regarding a clinical observation that can be derived using the thermal description of the eye. Our aim is to detect the malfunction of the ciliaris muscle influencing the bend of the eye lens which makes traditional dioptre measurement inaccurate. This malfunction is caused by the excessive activation of the muscle which can be tracked down by checking the temperature of the eye on thermal image about them. Thus, we consider somatoinfra (high quality thermal) images for detection with specialized machine learning approaches to this novel problem.
  • Keywords
    learning (artificial intelligence); medical image processing; object detection; ciliaris muscle; clinical observation; excessive activation detection; eye lens; human eye; somatoinfra images; specialized machine learning approaches; thermal image processing; traditional dioptre measurement; Cameras; Feature extraction; Lenses; Machine learning; Muscles; Support vector machine classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Machine Intelligence and Informatics (SAMI), 2011 IEEE 9th International Symposium on
  • Conference_Location
    Smolenice
  • Print_ISBN
    978-1-4244-7429-5
  • Type

    conf

  • DOI
    10.1109/SAMI.2011.5738899
  • Filename
    5738899