Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-painting

doi:doi:10.57702/g313sbd5

Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-painting

The dataset provided by the organizers consisted of 84000 (200, 400) fingerprint images generated using Anguli: Synthetic Fingerprint Generator. Those images were then artificially degraded by adding a background and random transformations (blur, brightness, contrast, elastic transformation, occlusion, scratch, resolution, rotation).

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The json representation of the dataset with its distributions based on DCAT.
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Cite this as

Youness MANSAR (2024). Dataset: Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-painting. https://doi.org/10.57702/g313sbd5

DOI retrieved: December 2, 2024

Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Youness MANSAR
Homepage	https://github.com/CVxTz/fingerprint_denoising