The week's pick
Reseach Article
Iris Recognition using Self Mutated Hybrid Wavelet Transform using Cosine, Haar, Hartley and Slant Transforms with Partial Energies of Transformed Iris Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 139 - Number 11 |
| Year of Publication: 2016 |
| Authors: Tejas H. Jadhav, Jaya H. Dewan |
10.5120/ijca2016909438
|
Tejas H. Jadhav, Jaya H. Dewan . Iris Recognition using Self Mutated Hybrid Wavelet Transform using Cosine, Haar, Hartley and Slant Transforms with Partial Energies of Transformed Iris Images. International Journal of Computer Applications. 139, 11 ( April 2016), 36-40. DOI=10.5120/ijca2016909438
Abstract
The paper presents iris recognition technique based on the concept of Energy Compaction. Compaction is done by using the partial energies of transformed iris images. Various Self mutated hybrid wavelet transforms (SMHWT) namely ‘Cosine-Haar’, ‘Cosine-Hartley’, and ‘Cosine-Slant’ are used to generate feature vector of iris images. The important task is reducing the size of feature vector so that the performance of system can be increased. The reduction of size of feature vector is achieved by using the concept of partial energies. The size of feature vector reduces immensely for 99%, 98%, 97% and 96% of energy. The size of feature vector is extremely large while considering all the coefficients of transformed iris images for 100% of energy which leads more computation. System gives better performance when partial energies are considered. The proposed technique is tested on Palacky University Iris Database. Genuine Acceptance Rate (GAR) is used as a metric to test the performance of the proposed Iris recognition technique. The self mutated hybrid wavelet transform of ‘Cosine-Haar’ gives preeminent GAR value as compared to other transforms considered. Results show the proposed technique gives better performance in terms of accuracy by considering partial energies as compared to 100% energy.
References
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- Dr.Sudeep Thepade, Jaya H. Dewan, “Image Compression Using Hybrid Wavelet Transform with Varying Proportions of Cosine, Haar, Walsh and Kekre Transforms with Assorted Color Spaces”, 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT),2014
- Dr. H. B. Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal, “Iris Recognition using Texture Features Extracted from Walshlet Pyramid”, ACM-International Conference and Workshop on Emerging Trends in Technology (ICWET 2011). Thakur College of Engg. And Tech., Mumbai, 26-27 Feb 2011.
- Dr. Sudeep Thepade, Pushpa R. Mandal, Sachin Jadhav,”Performance Comparison of Novel Iris Recognition Techniques Using Partial Energies of Transformed Iris Images and Enegy CompactionWith Hybrid Wavelet Transforms”, Annual IEEE India Conference (INDICON),2015
- Dr. H. B. Kekre, Dr. Tanuja K. Sarode, Sudeep D. Thepade and Ms. Sonal Shroff, "Instigation of Orthogonal Wavelet Transforms using walsh, Cosine, Hartley, Kekre Transforms and their use in Image Compression", (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011.
- PalackyUniversityIrisDatabase,http://www.advancesourcecode.com/irisdatabase.asp.(Referred on 4 January 2016).
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