Iris Image Recognition
Wavelet Filter-banks Based Iris Feature Extraction Schemes
Published on 27. May 2014
Book
Paperback/Softback
XIII, 84 pages
978-3-319-06766-7 (ISBN)
Description
This book provides the new results in wavelet filter banks based feature extraction, and the classifier in the field of iris image recognition. It provides the broad treatment on the design of separable, non-separable wavelets filter banks, and the classifier. The design techniques presented in the book are applied on iris image analysis for person authentication. This book also brings together the three strands of research (wavelets, iris image analysis and classifier). It compares the performance of the presented techniques with state-of-the-art available schemes. This book contains the compilation of basic material on the design of wavelets that avoids reading many different books. Therefore, it provides an easier path for the new-comers, researchers to master the contents. In addition, the designed filter banks and classifier can also be effectively used than existing filter-banks in many signal processing applications like pattern classification, data-compression, watermarking, denoising etc. that will give the new directions of the research in the relevant field for the readers.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
16 s/w Abbildungen, 17 farbige Abbildungen
XIII, 84 p. 33 illus., 17 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 6 mm
Weight
166 gr
ISBN-13
978-3-319-06766-7 (9783319067667)
DOI
10.1007/978-3-319-06767-4
Schweitzer Classification
Other editions
Additional editions
Amol D. Rahulkar | Raghunath S. Holambe
Iris Image Recognition
Wavelet Filter-banks Based Iris Feature Extraction Schemes
E-Book
05/2014
1st Edition
Springer
€53.49
Available for download
Persons
Dr. Aswini Kumar Samantaray received his B.Tech. and M.Tech. degree in electronics and communication engineering from Biju Patanaik University of Technology, Odisha, India in 2008 and 2012 respectively. He received his Ph.D. degree from National Institute of Technology Goa (NIT Goa), India in 2022. He worked as an Assistant Professor with the C. V. Raman College of Engineering from 2008 to 2018. He is currently working as an assistant professor with electronics and communication engineering, Vignan's Foundation for Science, Tecchnology and Research, Guntur, India. His research interests include the design of wavelets and filter-banks, image processing, and FPGA accelerators.
Dr. Amol D. Rahulkar received the B.E. degree in instrumentation engineering from the Shri Guru Gobind Singhji (SGGS) Institute of Engineering and Technology, Nanded, India, in 2000, the M.Tech. degree from the Indian Institute of Technology (IIT) Kharagpur, India, in 2002, and the Ph.D. degree from the SGGS Institute of Engineering and Technology, Nanded, affiliated to Swami Ramanand Teerth Marathwada University Nanded, India, in 2013. He is currently working as an Associate Professor with the Department of Electrical and Electronics Engineering, National Institute of Technology Goa (NIT Goa), India. His current research interests include the design of wavelets and filter-banks, digital signal processing, image processing, biometrics, FPGA accelerators, and soft-computing.
Content
Introduction.- Features Based on Triplet Half-band Wavelet Filter-banks.- Combined Directional Wavelet Filter-banks Based Features.- Iris Representation by Combined Hybrid Directional Wavelet Filter-banks.- Ordinal Measures Based on Directional Ordinal Wavelet Filters.