Biometric Identification Technologies Based on Modern Data Mining Methods

Modern biometric identification, examined chapter by chapter

Biometric Identification Technologies Based on Modern Data Mining Methods is an edited research volume that looks closely at how biometric systems are built, tested, and improved. The subject is broad, but the focus stays practical: face recognition, gait, keyboard dynamics, handwriting, palm features, stereo imaging, multimodal smartphone authentication, and ear-shape analysis all appear in the table of contents.

The result is a book that connects biometric theory with current applied research. Instead of treating identification as a single technique, the collection shows how different biometric signals behave, how they are measured, and how data mining methods can support more reliable authentication.

What the book covers

• static and behavioral biometric characteristics
• image-based identification methods
• gait and handwriting analysis
• keyboard and smartphone-based authentication
• palm, face, and ear biometrics
• approaches that use modern data analysis and recognition methods

Who it is for

This title is aimed at students, analysts, scientists, developers, and professionals working in intelligent information processing, information security, and real-time identification systems. It also suits readers who want a structured overview of contemporary biometric research rather than a general introduction.

Why it stands out

Because the chapters are written as individual research studies, the book gives readers a multi-angle view of biometrics in practice. That makes it especially useful for anyone comparing identification methods or tracking how the field is evolving across different modalities.