MatTag: Practical material tagging using visual fingerprints

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00643905" target="_blank" >RIV/67985556:_____/25:00643905 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

MatTag: Practical material tagging using visual fingerprints

Original language description

Assessment of material properties is essential for tasks such as similar material retrieval or swatch comparison in industrial design, manufacturing, and quality control. While many material similarity measures exist, they often fail to align with human perception. In this paper, we introduce a novel smartphone application using a machine learning model that leverages a perceptual representation known as the visual fingerprint of materials—linking image-based measurements to intuitive, human-understandable attributes. Trained on human ratings collected through psychophysical studies, the model can predict a material’s visual fingerprint using just two photographs captured under different lighting conditions. The application employ this model to assess any planar material sample using only a printed registration template and a flashlight. The app captures two photographs and predicts the material’s perceptual attributes. We demonstrate several practical use cases, including building personal material databases, retrieving visually similar materials, and exploring materials that match user-defined perceptual criteria. By enabling perceptually grounded comparisons and metadata extraction, our application provides a standardized representation of material appearance. This marks a step toward more intuitive and interoperable use of material properties across diverse digital environments.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

<a href="/en/project/GA22-17529S" target="_blank" >GA22-17529S: Visual fingerprint of material appearance</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the MANER Conference Mainz/Darmstadt 2025 (MANER 2025)

ISBN

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ISSN

1613-0073

e-ISSN

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Number of pages

11

Pages from-to

4

Publisher name

CEUR-WS

Place of publication

Germany

Event location

Mainz/Darmstadt

Event date

Jun 29, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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