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
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;
Conference_Titel :
Applied Machine Intelligence and Informatics (SAMI), 2011 IEEE 9th International Symposium on
Conference_Location :
Smolenice
Print_ISBN :
978-1-4244-7429-5
DOI :
10.1109/SAMI.2011.5738899
