Call for Paper - March 2023 Edition
IJCA solicits original research papers for the March 2023 Edition. Last date of manuscript submission is February 20, 2023. Read More

Iris Recognition using Self Mutated Hybrid Wavelet Transform using Cosine, Haar, Hartley and Slant Transforms with Partial Energies of Transformed Iris Images

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Tejas H. Jadhav, Jaya H. Dewan
10.5120/ijca2016909438

Tejas H Jadhav and Jaya H Dewan. 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 139(11):36-40, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Tejas H. Jadhav and Jaya H. Dewan},
	title = {Article: Iris Recognition using Self Mutated Hybrid Wavelet Transform using Cosine, Haar, Hartley and Slant Transforms with Partial Energies of Transformed Iris Images},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {11},
	pages = {36-40},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

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

  1. Dr. Sudeep Thepade, Pushpa R. Mandal ,“Energy Compaction based Novel Iris Recognition Techniques using Partial Energies of Transformed Iris Images with Cosine, Walsh, Haar, Kekre, Hartley Transforms and their Wavelet Transforms”,Annual IEEE India Conference (INDICON),2014.
  2. Dr.Sudeep Thepade, Jaya H. Dewan, “Image Compression using Cosine – Slant Hybrid Wavelet Transform with Assorted Color Spaces”, International Journal of Computer Applications (0975 – 8887) Volume 73– No.7, July 2013.
  3. Dr. Sudeep D. Thepade, Pooja Bidwai, “Iris Recognition using Fractional Coefficients of Transforms, Wavelet Transforms and Hybrid Wavelet Transforms”, International Conference on Control, Computing, Communication and Materials (ICCCCM), 2011.
  4. Ameya Deshpande, Sumitkumar Dubey, Hrushikesh Shaligram, Aditya Potnis, Satishkumar Chavan,“Iris Recognition System using Block Based Approach with DWT and DCT”, Annual IEEE India Conference (INDICON), 2014.
  5. Swati Dhage, Sushma Hegde, Manikantan K, S. Ramchandram, “ DWT based feature extraction and Randon transform based contrast enhancement for improved Iris recognition”, International conference on advanced computing technologies and applications, 2015.
  6. 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
  7. 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.
  8. 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
  9. 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.
  10. PalackyUniversityIrisDatabase,http://www.advancesourcecode.com/irisdatabase.asp.(Referred on 4 January 2016).

Keywords

Iris Recognition, Feature Vector, Genuine Acceptance Rate, Energy Compaction, Self Mutated Hybrid Wavelet Transform, Cosine transform, Haar Transform, Hartley Transform, Slant Transform.