國立高雄大學圖資館 |

登入

回首頁

Multimodal biometric identification system :case study of real-time implementation /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Multimodal biometric identification system :Sampada Dhole and Vinayak Bairagi.
其他題名:	case study of real-time implementation /
作者:	Dhole, Sampada,
其他作者:	Bairagi, Vinayak,
面頁冊數:	x, 131 pages :illustrations ;24 cm.
附註:	"A Chapman & Hall Book" - from cover.
標題:	Biometric identificationCongresses.Technological innovations
ISBN:	9781032665993

Multimodal biometric identification system :case study of real-time implementation /
Dhole, Sampada,

Multimodal biometric identification system :case study of real-time implementation /Sampada Dhole and Vinayak Bairagi. - First edition. - x, 131 pages :illustrations ;24 cm.

"A Chapman & Hall Book" - from cover.

Includes bibliographical references and index.

"This book presents a novel method of multimodal biometric fusion using a random selection of biometrics, which covers a new method of feature extraction, a new framework of sensor level and feature level fusion. Most of the biometric systems presently use unimodal systems which have several limitations. Multimodal systems can increase the matching accuracy of a recognition system. This monograph shows how the problems of unimodal systems can be efficiently dealt with and focuses on multimodal biometric identification and sensor-level feature-level fusion. It discusses fusion in biometric systems to improve performance. Presents a random selection of biometrics to ensure that the system is interacting with a live user. Offers a compilation of all techniques used for unimodal as well as multimodal biometric identification systems, elaborated with required justification & interpretation with case studies, suitable figures, tables & graphs etc. Shows that for feature level fusion using contourlet transform features with LDA for dimension reduction attains more accuracy compared to block variance features. Includes contribution in Feature Extraction & Pattern Recognition for increase in accuracy of the system. Explains contourlet transform as the best modality-specific feature extraction algorithms for fingerprint, face and palmprint. This book is for researchers, scholars and students of Computer Science, Information Technology, Electronics and Electrical Engineering, Mechanical Engineering, and people working on biometrics applications"--

ISBN: 9781032665993

LCCN: 2024021492Subjects--Topical Terms:

445903
Biometric identification
--Technological innovations--Congresses.

LC Class. No.: TK7882.B56 / D49 2025

Dewey Class. No.: 006.2/48

Multimodal biometric identification system :case study of real-time implementation /
LDR:03347cam 2200457 i 4500 001 693098
003 OCoLC
005 20260624101730.0
006 m o d
007 cr cnu---unuuu
008 260625t20252025flua ob 001 0 eng
010 $a 2024021492
020 $a 9781032665993 $q electronic book
020 $a 1032665998 $q electronic book
020 $a 9781040148136 $q electronic book
020 $a 1040148131 $q electronic book
020 $z 9781032660585 $q hardcover
020 $z 9781032665979 $q paperback
020 $a 9781040148235 $q ebook
020 $a 1040148239
029 1 $a AU@ $b 000077836540
035 $a (OCoLC)1455336941
035 $a on1455336941
040 $a DLC $b eng $e rda $c DLC $d OCLCO $d YDX $d OCLCO $d DLC $d OCLCL
042 $a pcc
049 $a NUKM
050 0 4 $a TK7882.B56 $b D49 2025
082 0 0 $a 006.2/48 $2 23/eng/20240907 $1 https://id.oclc.org/worldcat/ddc/E37kXPGHmfPMDqp3H7wHm9DW6j
100 1 $a Dhole, Sampada, $e author. $3 1009500
245 1 0 $a Multimodal biometric identification system : $b case study of real-time implementation / $c Sampada Dhole and Vinayak Bairagi.
250 $a First edition.
264 1 $a Boca Raton, FL : $b CRC Press, $c 2025.
264 4 $c ©2025
300 $a x, 131 pages : $b illustrations ; $c 24 cm.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a "A Chapman & Hall Book" - from cover.
504 $a Includes bibliographical references and index.
520 $a "This book presents a novel method of multimodal biometric fusion using a random selection of biometrics, which covers a new method of feature extraction, a new framework of sensor level and feature level fusion. Most of the biometric systems presently use unimodal systems which have several limitations. Multimodal systems can increase the matching accuracy of a recognition system. This monograph shows how the problems of unimodal systems can be efficiently dealt with and focuses on multimodal biometric identification and sensor-level feature-level fusion. It discusses fusion in biometric systems to improve performance. Presents a random selection of biometrics to ensure that the system is interacting with a live user. Offers a compilation of all techniques used for unimodal as well as multimodal biometric identification systems, elaborated with required justification & interpretation with case studies, suitable figures, tables & graphs etc. Shows that for feature level fusion using contourlet transform features with LDA for dimension reduction attains more accuracy compared to block variance features. Includes contribution in Feature Extraction & Pattern Recognition for increase in accuracy of the system. Explains contourlet transform as the best modality-specific feature extraction algorithms for fingerprint, face and palmprint. This book is for researchers, scholars and students of Computer Science, Information Technology, Electronics and Electrical Engineering, Mechanical Engineering, and people working on biometrics applications"-- $c Provided by publisher.
588 $a Description based on online resource; title from digital title page (viewed on November 18, 2024).
650 0 $a Biometric identification $x Technological innovations $v Congresses. $3 445903
650 6 $a Identification biométrique $x Innovations $0 (CaQQLa)201-0379286 $v Éttudes de cas. $0 (CaQQLa)201-0376950 $3 1009527
700 1 $a Bairagi, Vinayak, $e author. $3 845715
776 0 8 $i Print version: $a Dhole, Sampada. $t Multimodal biometric identification system $b First edition. $d Boca Raton : C&H/CRC Press, 2025 $z 9781032660585 $w (DLC) 2024021491
994 $a C0 $b TWNUK