Signal and Image Processing for Biometrics

1. Front Matter

   Pages i-x

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2. Data and Information Dimensionality in Non-cooperative Face Recognition

   • Geert Verdoolaege, John Soldera, Thiarlei Macedo, Jacob Scharcanski

   Pages 1-35

3. Remote Identification of Faces

   • Vishal M. Patel, Jie Ni, Rama Chellappa

   Pages 37-56

4. Biometric Identification from Facial Sketches of Poor Reliability: Comparison of Human and Machine Performance

   • H. Proença, J. C. Neves, J. Sequeiros, N. Carapito, N. C. Garcia

   Pages 57-75

5. Recognizing Altered Facial Appearances Due to Aging and Disguise

   • Richa Singh

   Pages 77-106

6. Using Score Fusion for Improving the Performance of Multispectral Face Recognition

   • Yufeng Zheng

   Pages 107-128

7. Unconstrained Ear Processing: What is Possible and What Must Be Done

   • Silvio Barra, Maria De Marsico, Michele Nappi, Daniel Riccio

   Pages 129-190

8. Feature Quality-Based Unconstrained Eye Recognition

   • Zhi Zhou, Eliza Yingzi Du, N. Luke Thomas

   Pages 191-207

9. Speed-Invariant Gait Recognition

   • Yasushi Makihara, Akira Tsuji, Yasushi Yagi

   Pages 209-229

10. Quality Induced Multiclassifier Fingerprint Verification Using Extended Feature Set

    • Mayank Vatsa

    Pages 231-254

11. Quality Measures for Online Handwritten Signatures

    • Nesma Houmani, Sonia Garcia-Salicetti

    Pages 255-283

12. Human Tracking in Non-cooperative Scenarios

    • Kamil Grabowski, Wojciech Sankowski

    Pages 285-331

This volume offers a guide to the state of the art in the fast evolving field of biometric recognition to newcomers and experienced practitioners. It is focused on the emerging strategies to perform biometric recognition under uncontrolled data acquisition conditions. The mainstream research work in this field is presented in an organized manner, so the reader can easily follow the trends that best suits her/his interests in this growing field. The book chapters cover the recent advances in less controlled / covert data acquisition frameworks, segmentation of poor quality biometric data, biometric data quality assessment, normalization of poor quality biometric data. contactless biometric recognition strategies, biometric recognition robustness, data resolution, illumination, distance, pose, motion, occlusions, multispectral biometric recognition, multimodal biometrics, fusion at different levels, high confidence automatic surveillance.

• Biometric Pattern Recognition
• Computer Forensics
• Contactless Data Acquisition
• Data Privacy
• Multimodal Biometrics
• Threat Assessment
• Uncontrolled Data Acquisition Conditions
• Varying Illumination Sources
• Visual Surveillance

From the book reviews:

“This book (consisting of 11 chapters) covers the state-of-the-art research on signal and image processing techniques used to support biometric recognition. … This book offers a good introduction to junior graduate students who are new to the field, and is also a good comprehensive reference for experienced practitioners.” (Mingchen Gao, Computing Reviews, August, 2014)

• Federal University of Rio Grande do Sul, Porto Alegre, Brazil

  Jacob Scharcanski

• IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal

  Hugo Proença

• Indiana University-Purdue University Indianapolis, Indianapolis, USA

  Eliza Du

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