dc.contributor.author | Atheesan, S | |
dc.contributor.author | Shanmugarajah, Y | |
dc.contributor.author | Ajanthan, T | |
dc.contributor.author | Ranathunga, L | |
dc.date.accessioned | 2017-03-11T10:08:04Z | |
dc.date.available | 2017-03-11T10:08:04Z | |
dc.identifier.uri | http://dl.lib.mrt.ac.lk/handle/123/12496 | |
dc.description.abstract | This paper describes an automatic system to identify glaucoma disease from funduscopic images by using digital image processing. Glaucoma caused by increase of pressure in eye and damages in optic nerve. Glaucoma tends to be grown and may not show until final stage. Through this system, doctors can easily identify patient’s condition quickly and do treatment. Rural people also will get advantage through this system. Glaucoma is identified through cup to disc ratio (CDR) calculation and orientation of the blood vessels in this system. For that Optical disk’s inner circle (cup) and outer circle (disc) is extracted. From that radius is calculated. The outer and inner circles are extracted by using average and maximum grey level pixels respectively with the use of histogram. Then find contours and draw circle which is best fitting the contours. The radius of cup and disc are found. After calculating CDR, the abnormal image can be found if CDR exceeds a particular threshold value. Otherwise it is normal image. The system extracts the blood vessels and through the orientation of the blood vessel glaucoma is identified. | en_US |
dc.language.iso | en | en_US |
dc.subject | Glaucoma | en_US |
dc.subject | Funduscopic Image | |
dc.subject | Image Processinng | |
dc.subject | Cup Disc Ratio | |
dc.title | Automatic Glaucoma Detection by Using Funduscopic Images | en_US |
dc.type | Conference-Full-text | en_US |
dc.identifier.faculty | IT | en_US |
dc.identifier.department | Department of Information Technology | en_US |
dc.identifier.year | 2015 | en_US |
dc.identifier.conference | ITRU RESEARCH SYMPOSIUM | en_US |
dc.identifier.place | UNIVERSITY OF MORATUWA | en_US |
dc.identifier.pgnos | 39-45 | en_US |
dc.identifier.email | atheesan91@gmail.com | en_US |
dc.identifier.email | yashoshan@gmail.com | en_US |
dc.identifier.email | ajanthan89274@gmail.com | en_US |
dc.identifier.email | lochandaka@uom.lk | en_US |