Adaptive Iris Segmentation

Abiyev, Rahib H.; Kilic, Kemal Ihsan

doi:10.1007/978-3-642-02617-1_10

Cited by 6 publications

(1 citation statement)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To detect the upper position of the pupil area, in this research we use a segmentation approach based on the Otsu threshold [28]. Therefore, the Gaussian filter was applied to the eye image using Eq.…”

Section: Pupil and Upper Eyelid Detectionmentioning

confidence: 99%

Electric Wheelchair Control Mechanism Using Eye-mark Key Point Detection

Pangestu¹,

Utaminingrum²

2020

IJIES

View full text Add to dashboard Cite

People with deficiency hands and feet, especially people with multiple disabilities has difficulty for navigation. Therefore, this research proposed an approach to help them using an electric wheelchair and control it using their eyeball movements. However, eyeball movement detection is still a problem due to the lack of standardized methods such as low accuracy for several gazes especially for downward and forward movements that caused by failure tracking mechanisms. Failure tracking mechanism mostly caused by failure pupil detection and tracking processes. According to the conducted research, there is a relation between eyeball movement and eyelid movement. Due to the relation, it can be concluded that the movement of the eyeball can be detected by utilize the eyelid movement without using the tracking mechanism. Hence, in this research, we propose an approach to detect the five movements of the eyeball using Eye-mark based on contour and edge detection. Our proposed method produces a brisk result with 91,2% of accuracy and better computational time compared with other marking methods. Accordingly, it is interesting on how to relate between eyeball movements and electric wheelchair navigation mechanism.

show abstract

Section: Pupil and Upper Eyelid Detectionmentioning

confidence: 99%