Segmentation and Separation of Overlapped Latent Fingerprints

1. Front Matter

   Pages i-x

   PDF

2. Latent Fingerprint Matching Systems

   • Branka Stojanović, Oge Marques, Aleksandar Nešković

   Pages 1-8

3. Latent Fingerprint Datasets

   • Branka Stojanović, Oge Marques, Aleksandar Nešković

   Pages 9-20

4. Overlapped Latent Fingerprints Segmentation: Problem Definition

   • Branka Stojanović, Oge Marques, Aleksandar Nešković

   Pages 21-28

5. Machine Learning Based Segmentation of Overlapped Latent Fingerprints

   • Branka Stojanović, Oge Marques, Aleksandar Nešković

   Pages 29-34

6. Overlapped Latent Fingerprints Separation: Problem Definition

   • Branka Stojanović, Oge Marques, Aleksandar Nešković

   Pages 35-44

7. Machine Learning Based Separation of Overlapped Latent Fingerprints

   • Branka Stojanović, Oge Marques, Aleksandar Nešković

   Pages 45-51

This Springerbrief presents an overview of problems and technologies behind segmentation and separation of overlapped latent fingerprints, which are two fundamental steps in the context of fingerprint matching systems. It addresses five main aspects: (1) the need for overlapped latent fingerprint segmentation and separation in the context of fingerprint verification systems; (2) the different datasets available for research on overlapped latent fingerprints; (3) selected algorithms and techniques for segmentation of overlapped latent fingerprints; (4) selected algorithms and techniques for separation of overlapped latent fingerprints; and (5) the use of deep learning techniques for segmentation and separation of overlapped latent fingerprints.


By offering a structured overview of the most important approaches currently available, putting them in perspective, and suggesting numerous resources for further exploration, this book gives its readers a clear path forlearning new topics and engaging in related research. Written from a technical perspective, and yet using language and terminology accessible to non-experts, it describes the technologies, introduces relevant datasets, highlights the most important research results in each area, and outlines the most challenging open research questions.

This Springerbrief targets researchers, professionals and advanced-level students studying and working in computer science, who are interested in the field of fingerprint matching and biometrics. Readers who want to deepen their understanding of specific topics will find more than one hundred references to additional sources of related information.

• Biometrics
• Latent fingerprints
• Overlapped fingerprint separation
• Overlapped fingerprint segmentation
• Fingerprint verification
• Fingerprint datasets
• Machine Learning
• Neural Networks
• Deep Learning
• Convolutional Neural Networks
• Forensics

• Vlatacom Research and Development Institute Ltd Belgrade, Belgrade, Serbia

  Branka Stojanović

• College of Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA

  Oge Marques

• School of Electrical Engineering, University of Belgrade, Belgrade, Serbia

  Aleksandar Nešković

Policies and ethics