Multimodal Biometric Identification System: Case Study of Real-Time Implementation
暫譯: 多模態生物識別系統：即時實施案例研究

Dhole, Sampada, Bairagi, Vinayak

Multimodal Biometric Identification System: Case Study of Real-Time Implementation
  • 出版商: CRC
  • 出版日期: 2026-07-20
  • 售價: $2,560
  • 貴賓價: 9.5 折 $2,432
  • 語言: 英文
  • 頁數: 132
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032665971
  • ISBN-13: 9781032665979
  • 相關分類: 影像辨識 Image-recognition

    • 尚未上市，無法訂購

商品描述

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 dealt with efficiently, 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 and interpretation with case studies, suitable figures, tables, graphs, and so on.

- Shows that for feature-level fusion using contourlet transform features with LDA for dimension reduction attains more accuracy compared to that of block variance features.

- Includes contribution in feature extraction and pattern recognition for an increase in the 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 biometric applications.

商品描述(中文翻譯)

這本書提出了一種使用隨機選擇生物特徵的多模態生物識別融合新方法，涵蓋了一種新的特徵提取方法以及傳感器層級和特徵層級融合的新框架。目前大多數生物識別系統使用單模態系統，這些系統存在若干限制。多模態系統可以提高識別系統的匹配準確性。本專著展示了如何有效解決單模態系統的問題，並專注於多模態生物識別和傳感器層級、特徵層級的融合。它討論了生物識別系統中的融合以改善性能。

- 提出了隨機選擇生物特徵的方法，以確保系統與活用戶進行互動。
- 提供了單模態和多模態生物識別系統所使用的所有技術的彙編，並附有必要的理由和解釋，包含案例研究、適當的圖形、表格、圖表等。
- 顯示使用輪廓變換（contourlet transform）特徵與線性判別分析（LDA）進行特徵層級融合以降維，與區塊方差特徵相比，能達到更高的準確性。
- 包含在特徵提取和模式識別方面的貢獻，以提高系統的準確性。
- 解釋了輪廓變換作為指紋、臉部和掌紋的最佳模態特定特徵提取算法。

這本書適合計算機科學、資訊技術、電子與電機工程、機械工程的研究人員、學者和學生，以及從事生物識別應用的人士。

作者簡介

Sampada Dhole has completed his PhD in Electronics from Bharati Vidyapeeth (Deemed to be University) College of Engineering, India, in 2017 with specialisation in Image Processing and Biometrics. Her research interest includes the Image Processing and Multimodal. She has published more than 30 research papers including 7 Scopus indexed. She has filed 2 patents and 1 copyright in her technical field. She has worked as a Reviewer for many International and National Conferences. She is working as Assistant Professor in the Department of E&TC at Bharati Vidyapeeth's College of Engineering for Women, SPPU, Pune, India. She has 21 years of teaching experience. She is a member of the Technical Society ISTE, India.

Vinayak Bairagi has completed ME (Electronics) from Sinhgad COE, Pune, India, in 2007 (1st Rank in SPPU). Savitribai Phule Pune University has awarded him a PhD degree in Engineering. He has teaching experience of 13 years and research experience of 8 years. He has filed 12 patents and 5 copyrights in his technical field. He has published more than 60 papers, of which 26 papers are in international journals. He has authored/edited more than eight books/book chapters with multiple publishing concerns and he is a reviewer for nine scientific journals. He has received grants from DST SERB, UoP-BUCD, GYTI. He has received more than 14 awards, which include the National Level Young Engineer Award (2014), the ISTE National level Young Researcher Award (2015) for his excellence in the field of engineering, and IETE M N SAHA Memorial Award-2018. He is a member of INENG (UK), IETE (India), ISTE (India), and IEI & BMS (India). He had worked on Image Compression at the College of Engineering, Pune, under Pune University. His main research interests include Medical Imaging, Machine Learning, Computer-Aided Diagnosis, and Medical Signal Processing. Currently, he is associated with the AISSMS Institute of Information Technology, Pune, India, as Professor in Electronics and Telecommunication Engineering. He is a recognised PhD guide in Electronics Engineering of Savitribai Phule Pune University. Presently he is guiding seven PhD students.

作者簡介(中文翻譯)

**Sampada Dhole**於2017年在印度Bharati Vidyapeeth（被認定為大學）工程學院獲得電子學博士學位，專攻影像處理和生物識別技術。她的研究興趣包括影像處理和多模態技術。她已發表超過30篇研究論文，其中7篇被Scopus索引。她在其技術領域申請了2項專利和1項著作權。她曾擔任多個國際和國內會議的審稿人。她目前在印度浦那的Bharati Vidyapeeth女子工程學院的電子與通信工程系擔任助理教授，擁有21年的教學經驗。她是印度技術學會ISTE的成員。

**Vinayak Bairagi**於2007年在印度浦那的Sinhgad工程學院獲得電子學碩士學位（在SPPU中排名第一）。Savitribai Phule Pune University授予他工程學博士學位。他擁有13年的教學經驗和8年的研究經驗。在其技術領域，他已申請12項專利和5項著作權。他已發表超過60篇論文，其中26篇發表在國際期刊上。他編著或編輯了超過八本書籍/書章，並擔任九本科學期刊的審稿人。他曾獲得DST SERB、UoP-BUCD、GYTI的資助。他獲得了超過14項獎項，包括2014年的全國青年工程師獎、2015年的ISTE全國青年研究者獎，以表彰他在工程領域的卓越表現，以及2018年的IETE M N SAHA紀念獎。他是INENG（英國）、IETE（印度）、ISTE（印度）和IEI & BMS（印度）的成員。他曾在浦那的工程學院從事影像壓縮的研究，隸屬於浦那大學。他的主要研究興趣包括醫學影像、機器學習、計算機輔助診斷和醫學信號處理。目前，他在印度浦那的AISSMS資訊技術學院擔任電子與通信工程教授。他是Savitribai Phule Pune University電子工程的認可博士生導師，目前指導七名博士生。

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