Novel Iris Recognition Techniques using Energy Compaction and Partial Energies of Transformed Iris Images with Cosine-Kekre and CosineHartley Hybrid Wavelet Transforms
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2014, Vol 3, Issue 9
Abstract
The paper presents novel Iris Recognition technique using Energy Compaction and Partial Energies of transformed iris images with the Hybrid wavelet transform namely ‘Cosine-Kekre’ and ‘Cosine-Hartley’ Hybrid wavelet transform. These two Hybrid wavelet transforms are applied on the iris images to obtain transformed iris images from which the feature vectors are generated in five different ways. The feature vector with 100% energy considers all of the coefficients of the transformed iris images to generate the feature vector so the size of feature vector is very large, in Energy compaction based feature vectors only the coefficients that hold 99%, 98%, 97% and 96% of energy are considered. Use of Partial energy reduces the feature vector size to a great extent and also it leads to lesser number of computations. The results tested using generic iris image database consisting 384 iris images have shown performance improvement in partial energy percentages with reduced feature vector size as indicated by higher Genuine Acceptance ratios as compared to 100% energy consideration.
Authors and Affiliations
Dr. Sudeep Thepade, Pushpa R. Mandal
Keywords
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