Title :
Efficient algorithms for detection of face, eye and eye state
Author :
Kalbkhani, Hashem ; Shayesteh, Mahrokh G. ; Mohsen Mousavi, Seyyed
Author_Institution :
Dept. of Electr. Eng., Urmia Univ., Urmia, Iran
Abstract :
Eye state analysis (open or closed) is an important step in fatigue detection. In this study, an efficient algorithm for eye state detection is proposed. At first, a new face detection method is presented for noisy images that finds the face area in the input image well. Then, novel algorithms for detection of eye region and eye state are introduced. The performance of the proposed method is evaluated on four different databases namely FERET, Aberdeen, IMM and CVL which contain more than 5700 images with different descents, positions, light conditions and glasses. The results show that the new method achieves more accuracy rate than the previously presented algorithms, while it does not need training data and is also computationally efficient.
Keywords :
eye; face recognition; Aberdeen database; CVL database; FERET database; IMM database; descents; eye region detection; eye state analysis; eye state detection; face detection method; fatigue detection; glasses; light conditions; noisy images; positions;
Journal_Title :
Computer Vision, IET
DOI :
10.1049/iet-cvi.2011.0091