posted on 2012-08-01, 13:13authored byMuhammad Shafi, Paul Chung
This paper proposes a hybrid method for eyes localization
in facial images. The novelty is in combining techniques
that utilise colour, edge and illumination cues to improve accuracy.
The method is based on the observation that eye regions have dark
colour, high density of edges and low illumination as compared
to other parts of face. The first step in the method is to extract
connected regions from facial images using colour, edge density and
illumination cues separately. Some of the regions are then removed
by applying rules that are based on the general geometry and shape
of eyes. The remaining connected regions obtained through these
three cues are then combined in a systematic way to enhance the
identification of the candidate regions for the eyes. The geometry
and shape based rules are then applied again to further remove the
false eye regions. The proposed method was tested using images from
the PICS facial images database. The proposed method has 93.7%
and 87% accuracies for initial blobs extraction and final eye detection
respectively.
History
School
Science
Department
Computer Science
Citation
SHAFI, M. and CHUNG, P.W.H., 2008. A hybrid method for eyes detection in facial images. IN: Proceedings of World Academy of Science, Engineering and Technology International Conference on Computer Science Singapore, 32, pp. 99 - 104