부산대학교 도서관

Nowadays a quadcopter is used in various applications, such as data collection, news broadcasting, surveying in hazardous areas, quadcopter racing competition, etc. Recently, a quadcopter movement control method has been implemented for people with disabilities by using a brain-computer interface (BCI). However, there are some limitations for BCI-based quadcopter movement control, for example, long response time in generating command signals, and unpredictable noise in human brain signals. In this paper, an image processing technique is proposed for quadcopter movement control. By detecting eye movements (i.e. forwarding gaze, left gaze, and right gaze), the image processing algorithm was implemented to distinguish the different states of eye movements and transform them into the quadcopter movement commands. This implemented technique aims to control a quadcopter without controlling by hand. Furthermore, the detection of eye movements for people who have ptosis or falling of the upper eyelid can be achieved by using the Circular Hough Transform algorithm.