A Hybrid Method for Eyes Detection in Facial Images
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.
[1] Hsu, R.L., Abdel-Mottaleb, M. & Jain, A. 2002, "Face detection in
color images", IEEE Transactions on Pattern Analysis and Machine
Intelligence , vol. 24, no. 5, pp. 696-706.
[2] PICS, 2003. Psychological Image Collection at Stirling (PICS image data
base). Available from http://pics.psych.stir.ac.uk/, University of Stirling
Psychology Department.
[3] Morimoto, C., Koons, D., Amir, A. & Flickner, M. 2000, "Pupil detection
and tracking using multiple light sources", Image and Vision Computing
, vol. 18, no. 4, pp. 331-335.
[4] Ebisawa, Y. & Satoh, S. 1993, "Effectiveness of pupil area detection technique
using two light sources and image difference method", Proceedings
of the 15th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society, 1993. , pp. 1268-1269.
[5] Chiang, C.C., Tai, W.K., Yang, M.T., Huang, Y.T. & Huang, C.J. 2003, "A
novel method for detecting lips, eyes and faces in real time", Real-Time
Imaging , vol. 9, no. 4, pp. 277-287.
[6] Kawaguchi, T., Rizon, M. & Hidaka, D. 2005, "Detection of eyes from
human faces by Hough transform and separability filter", Electronics and
Communications in Japan(Part II Electronics) , vol. 88, no. 5, pp. 29-39.
[7] Kumar, R.T., Raja, S.K. & Ramakrishnan, A.G. 2002, "Eye detection
using color cues and projection functions", Proceedings of International
Conference on Image Processing , vol. 3.
[8] Shafi, M. & Chung, P.W.H. 2008 "Eyes Extraction from Facial Images
Using Edge Density" Accepted in 7th IEEE International Conference on
Cybernetic Intelligent Systems.
[1] Hsu, R.L., Abdel-Mottaleb, M. & Jain, A. 2002, "Face detection in
color images", IEEE Transactions on Pattern Analysis and Machine
Intelligence , vol. 24, no. 5, pp. 696-706.
[2] PICS, 2003. Psychological Image Collection at Stirling (PICS image data
base). Available from http://pics.psych.stir.ac.uk/, University of Stirling
Psychology Department.
[3] Morimoto, C., Koons, D., Amir, A. & Flickner, M. 2000, "Pupil detection
and tracking using multiple light sources", Image and Vision Computing
, vol. 18, no. 4, pp. 331-335.
[4] Ebisawa, Y. & Satoh, S. 1993, "Effectiveness of pupil area detection technique
using two light sources and image difference method", Proceedings
of the 15th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society, 1993. , pp. 1268-1269.
[5] Chiang, C.C., Tai, W.K., Yang, M.T., Huang, Y.T. & Huang, C.J. 2003, "A
novel method for detecting lips, eyes and faces in real time", Real-Time
Imaging , vol. 9, no. 4, pp. 277-287.
[6] Kawaguchi, T., Rizon, M. & Hidaka, D. 2005, "Detection of eyes from
human faces by Hough transform and separability filter", Electronics and
Communications in Japan(Part II Electronics) , vol. 88, no. 5, pp. 29-39.
[7] Kumar, R.T., Raja, S.K. & Ramakrishnan, A.G. 2002, "Eye detection
using color cues and projection functions", Proceedings of International
Conference on Image Processing , vol. 3.
[8] Shafi, M. & Chung, P.W.H. 2008 "Eyes Extraction from Facial Images
Using Edge Density" Accepted in 7th IEEE International Conference on
Cybernetic Intelligent Systems.
@article{"International Journal of Information, Control and Computer Sciences:56507", author = "Muhammad Shafi and Paul W. H. Chung", title = "A Hybrid Method for Eyes Detection in Facial Images", abstract = "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.", keywords = "Erosion, dilation, Edge-density", volume = "2", number = "6", pages = "1990-6", }