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LATCHESS21: dataset of damaged chessboard lattice points (chessboard features) used to train LAPS detector (grayscale/21x21px)

Large dataset of damaged chessboard lattice points (chessboard features), generated automatically by modifying perfect 2D standard 8x8 chessboard grid, then evaluated on real photographs during detection process.

10% - perfect cases 10% - warped (random direction) 50% - evaluated during detection (real) 20% - mostly mistaken (objects) 10% - very hard (destroyed)

It contains the following subsets:

  • ok: correct chessboard lattice points
  • no: similar structures but not correct (convergent)

This dataset was used to train LAPS detector described in our article.

Publisher: RepOD

Publication year: 2018

Type of resource: Dataset

Area of study: Technology and engineering

License for files: CC0-1.0

Files in this dataset

Keywords

Authors

Author Affiliation
Czyzewski, Maciej A. 1) Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
Laskowski, Artur 1) Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland; 2) European Center for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
Wasik, Szymon 1) Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland; 2) European Center for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland; 3) Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland

Cite this dataset as:

Czyzewski, M.; Laskowski, A.; Wasik, S. (2018) LATCHESS21: dataset of damaged chessboard lattice points (chessboard features) used to train LAPS detector (grayscale/21x21px). RepOD. http://dx.doi.org/10.18150/repod.7606646

Publicly available in RepOD since: 2018-05-10 23:08 (CEST)

Download the dataset citation