{"data":{"id":"10.4121/94c42619-4192-4c41-9d57-b9f764761605","type":"dois","attributes":{"doi":"10.4121/94c42619-4192-4c41-9d57-b9f764761605","prefix":"10.4121","suffix":"94c42619-4192-4c41-9d57-b9f764761605","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Köşker, Arda","givenName":"Arda","familyName":"Köşker","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Data underlying the MSc thesis: Design and Evaluation of Methods for Synthetic and Heritage-Like Fingerprints"}],"publisher":"4TU.ResearchData","container":{},"publicationYear":2026,"subjects":[{"subject":"Electrical and Electronic Engineering","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"0906"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Engineering","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"09"},{"subject":"3D fingerprint synthesis"},{"subject":"terracotta"},{"subject":"heritage biometrics"},{"subject":"clay"}],"contributors":[{"name":"University of Twente, Electrical and Electronics Engineering","nameType":"Organizational","affiliation":[],"contributorType":"Other","nameIdentifiers":[]}],"dates":[{"date":"2026-01-26","dateType":"Issued"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.4121/94c42619-4192-4c41-9d57-b9f764761605.v1","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["script/.py wavefront/.obj markdown/.txt"],"version":"1","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"# Synthetic Heritage-Like Clay Impression Dataset (SHCID)# Author: Y. Arda Kosker (University of Twente)# Date: January 2026\u003cbr\u003e## 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.\u003cbr\u003e## 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).\u003cbr\u003e## 3. Technical Note on CompressionThe uncompressed dataset occupies approximately 40 GB of disk space. Please ensure sufficient disk space before extraction.\u003cbr\u003e## 4. Code \u0026amp; 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.\u003cbr\u003eRequirements: Python 3.x, NumPy, OpenCV, Trimesh, Matplotlib.\u003cbr\u003e## 5. License \u0026amp; 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.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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