Fully automated blink detection for uveal melanoma radiotherapy

Uveal melanom, being a widespread neoplasm in the eye, may cause vision defect, loss of the eye, even loss of life with the high level risk of metastasis. From past to the present there have been tried many treatment methods which are varying from enucleation at the end of treatment of the eye, to the medication with radiotherapy threatment in accordance with the status of the disease. Today, enucleation is the last way to apply, so radiotherapy occupies an important place. There is need for high-technology devices in radiotherapy treatment, the treatment is conducted sensitively with radioactive beam radiation. Some equipments used during operation like blepharostat and vacuum rings may lead some complications during operation and can make the patients have uncomfortable treatment. In this thesis, in order to eliminate the possible negative effects of therapy, we studied an algorithm which is for use in eye surgery, that can fix the therapy in accordance with the present instant state of iris and eyelids. This algorithm will be a real time system and will be based on the classification of the acquired image frames according to a learning algorithm. It is aimed that the speed of the algorithm is as close as possible to real time so that it can response instantly to any instant change in present eye state. The motivation of the study is based upon iris tracking, localization and blink detection which is now used frequently for human computer interface, fatique detector, face analysis topics. The principle of the study is based on the detection of eye state, i.e. open or closed, in varying lighting conditions by a linear classification on real-time video frames. In the study, iris is detected first, then some features which have low computational complexity and high classification performance are determined. Feature vectors are formed for bright and dark lighting conditions and these vectors were classified with linear discriminant analysis. We had successful results with chosen features and examined with cross validation method. There were no decremental effects of harder conditions.