Abstract
There are various Iris recognition and identification schemes known to produce exceptional results with very less errors and at times no errors at all but are patented. Many prominent researchers have given their schemes for either recognition of an Iris from an image and then identifying it from a set of available database so as to know who it belongs to. The Gabor filter is a preferred algorithm for feature extraction of Iris image but it has certain limitations, hence Principal Component Analysis (PCA) is used to overcome the limitations of the Gabor filter and provide a solution which achieves better results which are encouraging and provide a better solution to Gabor filters for Off Gaze images.
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Sayed, A., Sardeshmukh, M., Limkar, S. (2014). Improved Iris Recognition Using Eigen Values for Feature Extraction for Off Gaze Images. In: Satapathy, S., Avadhani, P., Udgata, S., Lakshminarayana, S. (eds) ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol II. Advances in Intelligent Systems and Computing, vol 249. Springer, Cham. https://doi.org/10.1007/978-3-319-03095-1_20
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DOI: https://doi.org/10.1007/978-3-319-03095-1_20
Publisher Name: Springer, Cham
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