Swarm intelligence for iris recognition / Zaheera Zainal Abidin.

By:

Abidin, Zaheera Zainal, 1977- [author.]

Material type: Text

TextPublisher: Boca Raton : CRC Press, Taylor & Francis Group, c 2021Edition: First editionDescription: ix, 135 pages : illustrations ; 23 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780367627478
9780367627508

Subject(s):

DDC classification:

006.4 23 ABI-S 2021 790337

Contents:

Human eye -- The first phase of iris recognition -- The second phase of iris recognition -- Swarm-inspired iris recognition.

Summary: "Iris recognition has been widely recognized as one of the most performing biometric system. The accuracy performance of iris recognition system is measured by FRR (False Reject Rate). FRR measures the genuine user who is incorrectly denied by the system due to the changes in iris features (such as aging and health condition) and external factors that affected the iris image to be high in noise rate. The external factors such as technical fault, occlusion, and source of lighting caused the image acquisition to produce distorted iris images problem hence incorrectly rejected by the biometric system. The current way of reducing FRR are wavelets and Gabor filters, cascaded classifiers, ordinal measure, multiple biometric modality and selection of unique iris features. Nonetheless, in the long duration of matching process, the previous methods unable to identify the user as a genuine since the iris structure itself produce a template changed due to aging. In facts, iris consists of unique features such as crypts, furrows, collarette, pigment blotches, freckles and pupil that are distinguishable among human. Previous research has been done in selecting the unique iris features however it shows low accuracy performance. Therefore, a new way of identifying and matching the iris template using nature-inspired algorithm is proposed in this book. As a conclusion, this book entitled as "Swarm Intelligence for Iris Recognition" brings an overview of iris recognition that naturally based on nature-inspired environment technology and provides benefits to the reader"-- Provided by publisher.

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Holdings ( 3 )
Title notes ( 5 )

Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Reference	Faculty of CS & IT Library Book Cart	Book	006.4 ABI-S 2021 790337 (Browse shelf(Opens below))	1	Not For Loan (Restricted Access)	790337
Books	Faculty of CS & IT Library Book Cart	Book	006.4 ABI-S 2021 790338 (Browse shelf(Opens below))	2	Available	790338
Books	Faculty of CS & IT Library Book Cart	Book	006.4 ABI-S 2021 790339 (Browse shelf(Opens below))	3	Available	790339

Total holds: 0

"A Science Publisher's book."

Originally presented as the author's thesis (doctoral)--Universiti Teknologi MARA, Shah Alam, 2016.

Includes bibliographical references and index.

Human eye -- The first phase of iris recognition -- The second phase of iris recognition -- Swarm-inspired iris recognition.

"Iris recognition has been widely recognized as one of the most performing biometric system. The accuracy performance of iris recognition system is measured by FRR (False Reject Rate). FRR measures the genuine user who is incorrectly denied by the system due to the changes in iris features (such as aging and health condition) and external factors that affected the iris image to be high in noise rate. The external factors such as technical fault, occlusion, and source of lighting caused the image acquisition to produce distorted iris images problem hence incorrectly rejected by the biometric system. The current way of reducing FRR are wavelets and Gabor filters, cascaded classifiers, ordinal measure, multiple biometric modality and selection of unique iris features. Nonetheless, in the long duration of matching process, the previous methods unable to identify the user as a genuine since the iris structure itself produce a template changed due to aging. In facts, iris consists of unique features such as crypts, furrows, collarette, pigment blotches, freckles and pupil that are distinguishable among human. Previous research has been done in selecting the unique iris features however it shows low accuracy performance. Therefore, a new way of identifying and matching the iris template using nature-inspired algorithm is proposed in this book. As a conclusion, this book entitled as "Swarm Intelligence for Iris Recognition" brings an overview of iris recognition that naturally based on nature-inspired environment technology and provides benefits to the reader"-- Provided by publisher.