Abstract
This paper presents a novel approach for the automatic localization of pupil in which multiscale edge detection approach has been employed as a preprocessing step to efficiently localize the pupil followed by a new feature extraction technique which is based on a combination of some multiscale feature extraction techniques. Then pupil is localized using histogram thresholding and filter mask which looks for the region that has the highest probability of having pupil. Here some effort has given for the removal of the effect of hairs on eyelashes and eye brows by the help of a region based averaging filtering. The proposed method is tested on CASIA database. Experimental results show that this method is comparatively accurate.
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Sahoo, N., Padhy, G., Bhoi, N., Rautaray, P. (2012). Automatic Localization of Pupil Using Histogram Thresholding and Region Based Mask Filter. In: Patnaik, S., Yang, YM. (eds) Soft Computing Techniques in Vision Science. Studies in Computational Intelligence, vol 395. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25507-6_6
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DOI: https://doi.org/10.1007/978-3-642-25507-6_6
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