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A hybrid method for eyes detection in facial images

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conference contribution
posted on 01.08.2012, 13:13 by Muhammad 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

Publisher

© World Academy of Science, Engineering and Technology (WASET)

Publication date

2008

Notes

This is a conference paper.

ISSN

2070-3740

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