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Kolektor Surface-Defect
2D Semantic Segmentation
Industry
|...
License: Unknown

Overview

The dataset is constructed from images of defected electrical commutators that were provided
and annotated by Kolektor Group d.o.o.. Specifically,
microscopic fractions or cracks were observed on the surface of the plastic embedding in electrical
commutators. The surface area of each commutator was captured in eight non-overlapping images.
The images were captured in a controlled environment.

The dataset consists of:

  • 50 physical items (defected electrical commutators)

  • 8 surfaces per item

  • Altogether 399 images:

    • 52 images of visible defect
    • 347 images without any defect
  • Original images of sizes:

    • width: 500 px
    • height: from 1240 to 1270 px
  • For training and evaluation images should be resized to 512 x 1408 px

For each item the defect is only visible
in at least one image, while two items have defects on two images, which means there were 52
images where the defects are visible. The remaining 347 images serve as negative examples with
non-defective surfaces.

Citation

Please use the following citation when referencing the dataset:

@article{Tabernik2019JIM,
  author = {Tabernik, Domen and {\v{S}}ela, Samo and Skvar{\v{c}}, Jure and
  Sko{\v{c}}aj, Danijel},
  journal = {Journal of Intelligent Manufacturing},
  title = {{Segmentation-Based Deep-Learning Approach for Surface-Defect Detection}},
  year = {2019},
  month = {May},
  day = {15},
  issn={1572-8145},
  doi={10.1007/s10845-019-01476-x}
}
Data Summary
Type
Image,
Amount
399
Size
97.59MB
Provided by
Kolektor Group d.o.o.
This team has more than 20 years of experience in the field of machine vision and we are the first provider of solutions for optical control in the region. We implemented more than 1000 machine vision systems in different industries.
| Amount 399 | Size 97.59MB
Kolektor Surface-Defect
2D Semantic Segmentation
Industry
License: Unknown

Overview

The dataset is constructed from images of defected electrical commutators that were provided
and annotated by Kolektor Group d.o.o.. Specifically,
microscopic fractions or cracks were observed on the surface of the plastic embedding in electrical
commutators. The surface area of each commutator was captured in eight non-overlapping images.
The images were captured in a controlled environment.

The dataset consists of:

  • 50 physical items (defected electrical commutators)

  • 8 surfaces per item

  • Altogether 399 images:

    • 52 images of visible defect
    • 347 images without any defect
  • Original images of sizes:

    • width: 500 px
    • height: from 1240 to 1270 px
  • For training and evaluation images should be resized to 512 x 1408 px

For each item the defect is only visible
in at least one image, while two items have defects on two images, which means there were 52
images where the defects are visible. The remaining 347 images serve as negative examples with
non-defective surfaces.

Citation

Please use the following citation when referencing the dataset:

@article{Tabernik2019JIM,
  author = {Tabernik, Domen and {\v{S}}ela, Samo and Skvar{\v{c}}, Jure and
  Sko{\v{c}}aj, Danijel},
  journal = {Journal of Intelligent Manufacturing},
  title = {{Segmentation-Based Deep-Learning Approach for Surface-Defect Detection}},
  year = {2019},
  month = {May},
  day = {15},
  issn={1572-8145},
  doi={10.1007/s10845-019-01476-x}
}
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