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Record Nr. |
UNINA9910299744003321 |
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Autore |
Rahulkar Amol D |
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Titolo |
Iris Image Recognition : Wavelet Filter-banks Based Iris Feature Extraction Schemes / / by Amol D. Rahulkar, Raghunath S. Holambe |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
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ISBN |
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Edizione |
[1st ed. 2014.] |
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Descrizione fisica |
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1 online resource (95 p.) |
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Collana |
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SpringerBriefs in Signal Processing, , 2196-4076 |
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Disciplina |
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Soggetti |
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Signal processing |
Image processing |
Speech processing systems |
Optical data processing |
System safety |
Signal, Image and Speech Processing |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Security Science and Technology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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 provide an easier path for the new-comers, researchers to |
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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. |
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