Data underlying the MSc thesis: Design and Evaluation of Methods for Synthetic and Heritage-Like Fingerprints

# Synthetic Heritage-Like Clay Impression Dataset (SHCID)# Author: Y. Arda Kosker (University of Twente)# Date: January 2026<br>## 1. OverviewThis dataset contains 1,120 synthetic 3D fingerprint models generated to evaluate matching algorithms under varying conditions. The models simulate both ideal (Clean) and real-world/heritage (Realistic) surface properties.<br>## 2. Dataset Structure- Identities: 80 unique identity runs (run_1 to run_80).- Variations per Identity: 14 models.- Data Splits: - Clean: Baseline models with full fingerprints and continuous surfaces. - Realistic: Models with partial fingerprints and surface cracks.- File Format: .obj (Wavefront 3D).- Physical Scale: 21.1 mm (W) x 28.4 mm (H).<br>## 3. Technical Note on CompressionThe uncompressed dataset occupies approximately 40 GB of disk space. Please ensure sufficient disk space before extraction.<br>## 4. Code &amp; GenerationThe provided Python scripts allow for the reproduction of the dataset:- main.py: The entry point for the generation pipeline.- MeshGenerator.py: Class definition managing the 3D construction logic.- myScripts/: Module containing mathematical foundations and procedural texture algorithms.<br>Requirements: Python 3.x, NumPy, OpenCV, Trimesh, Matplotlib.<br>## 5. License &amp; CitationThis work is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).If you use this data, please cite:Kosker, Y. Arda. "Design and Evaluation of Methods for Synthetic and Heritage-Like Fingerprints." Master's Thesis, University of Twente, 2026.