“We were very happy with the quality of the data that we purchased. It will assist our efforts to improve our product. The team at Unidata was very responsive to our needs, and provided the data format needed to complete our tasks. We are happy to state that Unidata delivers a high quality product in an effective and efficient manner.”
Commercial
Biometric Fingerprint Spoofing Dataset
Contains 5,000+ high-quality fingerprint images capturing real fingerprints and multiple fingerprint spoofing attack types, including print and replay scenarios. Designed for spoofing detection and liveness detection tasks, the fingerprint dataset provides labeled biometric data from different devices and fingers to train and evaluate biometric security and fingerprint recognition systems.
-
- People
- 100
-
- Photos
- 5000+
- Computer Vision
- Machine Learning
- Image Processing
- Security
- Anti-Spoofing
- Computer Vision
- Machine Learning
- Image Processing
- Security
- Anti-Spoofing
Contains 5,000+ high-quality fingerprint images capturing real fingerprints and multiple fingerprint spoofing attack types, including print and replay scenarios. Designed for spoofing detection and liveness detection tasks, the fingerprint dataset provides labeled biometric data from different devices and fingers to train and evaluate biometric security and fingerprint recognition systems.
- Computer Vision
- Machine Learning
- Image Processing
- Security
- Anti-Spoofing
-
- People
- 100
-
- Photos
- 5000+
Dataset Info
| Characteristic | Data |
| Description | Fingerprint images were captured via three attack types: print, real, and replay |
| Data types | Image |
| Tasks | Spoof Detection, Classification |
| Number of images | 5000+ |
| Number of files in a set | 30 (10 real, 10 print, 10 replay) |
| Labeling | Metadata (gender, age, finger, hand, shooting device, display device, paper) |
| Total number of people | 100 |
Fintech hit by 100K biometric spoofing attacks monthly
Discover how top fintechs prevent fraud — download our free white paper
Technical
Characteristics
| Characteristic | Data |
| Image Extension | JPG |
| Device | iPhone, Samsung, OPPO |
Dataset Use Cases
FAQs
Can I request a sample of the fingerprint dataset before purchasing?
Yes, a free sample of the fingerprint dataset is available for evaluation and testing. This allows you to review real fingerprints, fake fingerprints, and metadata structure before committing to the full dataset.
What types of annotations are provided with the dataset?
Each fingerprint image includes detailed metadata such as finger type, hand, gender, age, capture device, display device, and paper type. These labels support advanced pattern recognition, attack detection, and recognition performance analysis.
How was the data collected?
All fingerprint images were captured by the Unidata team in a rented studio using mobile devices under controlled conditions.
How are Unidata fingerprint datasets licensed?
Unidata datasets follow a dual-licensing model where free samples are provided for testing, while full datasets are available through purchase. This structure supports both experimentation and production-grade biometric technology development.
Do Unidata datasets comply with GDPR and data privacy laws?
Yes, all biometric datasets are curated in full compliance with GDPR and applicable data protection regulations. Data is collected ethically from legally permissible sources to ensure privacy and lawful usage.
How are biometric datasets stored and secured?
All fingerprint data is securely stored on AWS cloud infrastructure with controls aligned to ISO 27001 and ISO 27701 standards. This ensures strong biometric data protection, scalability, and secure access management.
How long does it take to receive the fingerprint spoofing dataset?
After submitting a request, the Unidata team reviews the requirements and completes documentation. Once signed and paid, the dataset is delivered within 3–10 days.
Why is spoof attack data important for training fingerprint recognition models?
Spoof attack examples allow machine learning models to understand the differences between authentic fingerprints and artificial replicas. This improves the robustness of biometric systems used in identity verification and access control applications.
Still have questions about using Unidata datasets?
Read our user-guides
Unidata Cases
Digital Tree Passport Annotation for Forest Mapping
- Forestry Monitoring & GIS
- 200,000 trees, 10 species classes
- 2 months
License Plate Annotation for Vehicle Recognition System
- 100,000 images with detailed license plate markup (bounding boxes, digits, regional symbols)
- 3 weeks
Sentiment Annotation for Brand Monitoring
- Marketing & Consumer Insights
- 12,000 text samples
- 7 weeks
Surveillance Video Annotation for Entrance Monitoring
- Surveillance & Security
- 90 minutes of video from three cameras, approximately 50-60 thousand frames
- 2 week
Similar Datasets
-
Commercial
- Facial Recognition
- Age Estimation
- Re-identification
- Security
- Computer Vision
Kids & Teens Aging Dataset (Ages 7-21)
The dataset was created for age estimation, age progression analysis, and facial aging studies in children and teenagers aged 7–21. This face image dataset includes photos annotated with the Monk Skin Tone (MST) scale, camera angle, whether the shot is a digital or physical (scanned) photo, accessories worn, blur, and background handling, alongside demographic metadata (gender, ethnicity, skin tone category).
8,039 Photos
536 People -
Commercial
- Identity Verification
- Computer Vision
- Machine Learning
- Biometric Recognition
- Security
Human Iris Images Biometric Dataset
High-quality iris dataset with 5,000+ JPG images from 5,000+ individuals, containing left and right eye captures for iris recognition and computer vision tasks. This eye iris dataset includes labeled images collected under visible light, with metadata (ID, eye, sex) to support training data for biometric recognition systems, iris segmentation, and iris pattern analysis.
5,000+ Images
5,000+ People -
Commercial
- Computer Vision
- Machine Learning
- Image Processing
- Security
- Anti-Spoofing
Multi-Material Fingerprint Spoofing Dataset
This fingerprint spoofing dataset contains fingerprint images, captured with a ZKTeco ZK9500 optical scanner and including real fingerprints and spoofing attacks created with alginate, plasticine, and silicone materials. The fingerprint dataset includes metadata (gender, age, finger, hand, device) and supports biometric security research, presentation attack detection, spoof detection, and fingerprint recognition model training.
100 People
4000+ Photos -
Commercial
- Facial Recognition
- Liveness Detection
- Security
- Anti-spoofing
- Computer Vision
Anti-Spoofing Replay PC Videos Dataset
High-quality replay attack dataset containing 4,714 PC-recorded video clips of real faces, designed for training and evaluating face recognition and liveness detection systems. This anti-spoofing videos dataset includes diverse attack scenarios, technical metadata (age, gender, ethnicity), and MP4/MOV formats to support spoofing detection, biometric security, and computer vision model development.
4,714 Videos
4,714 People -
Commercial
- Facial Recognition
- Liveness Detection
- Security
- Anti-spoofing
- Computer Vision
Anti-Spoofing Replay Phone Videos Dataset
This anti-spoofing dataset contains over 40,036 live facial video recordings captured on mobile devices to support replay attack detection and biometric anti-spoofing research. With paired video sets, MP4/MOV formats, and rich metadata such as age, gender, and ethnicity, it provides reliable training data for face antispoofing, liveness detection, and secure biometric authentication systems.
40,036 Videos
20,018 Sets -
Commercial
- Speech Analysis
- ASR
- Machine learning
- Data generation
- Audio Processing
Real vs Fake Human Voice – Deepfake Audio Dataset
Audio dataset containing 5,000 audio files featuring both genuine human recordings and AI-generated voice samples. Each set includes four speakers with multiple clips across M4A and MP3 formats. The dataset supports research in deepfake detection, generated speech analysis, and real vs fake human voice recognition tasks.
5,000 Audio
-
Commercial
- Facial Recognition
- Security
- Anti-spoofing
- Computer Vision
- Machine Learning
Kids Anti-Spoofing Dataset
The dataset provides 6,000 high-quality facial images of children aged 7–15 for face anti-spoofing and liveness detection tasks. This child safety dataset supports research in biometric systems, helping improve facial recognition accuracy, detect spoofing attacks, and build safer AI models for protecting kids in digital and identification environments.
6 000 Images
300 people -
Commercial
- Image Processing
- Machine Learning
- Hand Recognition
- Forensics
- Computer Vision
Open Palm Hand Images Dataset
This high-quality open palm dataset includes 179,052 annotated images collected from 29,842 people, with each set containing six palm photos, two printed-hand images, and two replay videos. Designed for hand recognition and computer vision research, it provides detailed metadata - age, gender, ethnicity, profession, device type, dominant hand, and jewelry status.
179,052 Images
29,842 People -
Commercial
- PII
- Data generation
- Security
- Anti-spoofing
- Computer Vision
Synthetic Printed Turkish Passports Dataset
It is a synthetic Turkish passports dataset containing 5,000 high-quality, AI-generated images. Labeled with detailed metadata - including passport ID, class, gender, and lighting - this dataset supports PII extraction, identity verification, and biometric recognition system training while maintaining strict data protection standards.
5000 Images
-
Commercial
- Facial Recognition
- iBeta
- Liveness Detection
- Security
- Anti-spoofing
- Computer Vision
iBeta Kids Dataset
It is a child safety dataset featuring over 46,000 short video samples of children across different age groups, recorded under varied lighting, devices, and conditions. It includes four main attack types: Real Person, 2D Mask, 3D Mask, and Replay, helping develop biometric systems that detect spoofing and ensure safe, accurate child identification.
45 600 Videos
60 People
Why Companies Trust Unidata's Datasets
Share your project requirements, we handle the rest. Every service is tailored, executed, and compliance-ready, so you can focus on strategy and growth, not operations.
Our Clients Love Us
Ready to get started?
Tell us what you need — we’ll reply within 24h with a free estimate
- Andrew
- Head of Client Success
— I'll guide you through every step, from your first
message to full project delivery
Thank you for your
message
We use cookies to enhance your experience, personalize content, ads, and analyze traffic. By clicking 'Accept All', you agree to our Cookie Policy.