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On the role of distance transformations in Baddeley’s Delta Metric

Carlos Lopez-Molina, Sara Iglesias-Rey, H. Bustince and Bernard De Baets (UGent)
(2021) INFORMATION SCIENCES. 569. p.479-495
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Abstract
Comparison and similarity measurement have been a key topic in computer vision for a long time. There is, indeed, an extensive list of algorithms and measures for image or subimage comparison. The superiority or inferiority of different measures is hard to scrutinize, especially considering the dimensionality of their parameter space and their many different configurations. In this work, we focus on the comparison of binary images, and study different variations of Baddeley’s Delta Metric, a popular metric for such images. We study the possible parameterizations of the metric, stressing the numerical and behavioural impact of different settings. Specifically, we consider the parameter settings proposed by the original author, as well as the substitution of distance transformations by regularized distance transformations, as recently presented by Brunet and Sills. We take a qualitative perspective on the effects of the settings, and also perform quantitative experiments on separability of datasets for boundary evaluation.
Keywords
Control and Systems Engineering, Theoretical Computer Science, Software, Information Systems and Management, Artificial Intelligence, Computer Science Applications, Image comparison, Binary image, Baddeley's Delta Metric, Distance transform, Generalized distance transform, HAUSDORFF DISTANCE, EDGE, ALGORITHM, IMAGES, RECOGNITION, COMPUTATION

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MLA
Lopez-Molina, Carlos, et al. “On the Role of Distance Transformations in Baddeley’s Delta Metric.” INFORMATION SCIENCES, vol. 569, 2021, pp. 479–95, doi:10.1016/j.ins.2021.05.034.
APA
Lopez-Molina, C., Iglesias-Rey, S., Bustince, H., & De Baets, B. (2021). On the role of distance transformations in Baddeley’s Delta Metric. INFORMATION SCIENCES, 569, 479–495. https://doi.org/10.1016/j.ins.2021.05.034
Chicago author-date
Lopez-Molina, Carlos, Sara Iglesias-Rey, H. Bustince, and Bernard De Baets. 2021. “On the Role of Distance Transformations in Baddeley’s Delta Metric.” INFORMATION SCIENCES 569: 479–95. https://doi.org/10.1016/j.ins.2021.05.034.
Chicago author-date (all authors)
Lopez-Molina, Carlos, Sara Iglesias-Rey, H. Bustince, and Bernard De Baets. 2021. “On the Role of Distance Transformations in Baddeley’s Delta Metric.” INFORMATION SCIENCES 569: 479–495. doi:10.1016/j.ins.2021.05.034.
Vancouver
1.
Lopez-Molina C, Iglesias-Rey S, Bustince H, De Baets B. On the role of distance transformations in Baddeley’s Delta Metric. INFORMATION SCIENCES. 2021;569:479–95.
IEEE
[1]
C. Lopez-Molina, S. Iglesias-Rey, H. Bustince, and B. De Baets, “On the role of distance transformations in Baddeley’s Delta Metric,” INFORMATION SCIENCES, vol. 569, pp. 479–495, 2021.
@article{8712254,
  abstract     = {{Comparison and similarity measurement have been a key topic in computer vision for a long time. There is, indeed, an extensive list of algorithms and measures for image or subimage comparison. The superiority or inferiority of different measures is hard to scrutinize, especially considering the dimensionality of their parameter space and their many different configurations. In this work, we focus on the comparison of binary images, and study different variations of Baddeley’s Delta Metric, a popular metric for such images. We study the possible parameterizations of the metric, stressing the numerical and behavioural impact of different settings. Specifically, we consider the parameter settings proposed by the original author, as well as the substitution of distance transformations by regularized distance transformations, as recently presented by Brunet and Sills. We take a qualitative perspective on the effects of the settings, and also perform quantitative experiments on separability of datasets for boundary evaluation.}},
  author       = {{Lopez-Molina, Carlos and Iglesias-Rey, Sara and Bustince, H. and De Baets, Bernard}},
  issn         = {{0020-0255}},
  journal      = {{INFORMATION SCIENCES}},
  keywords     = {{Control and Systems Engineering,Theoretical Computer Science,Software,Information Systems and Management,Artificial Intelligence,Computer Science Applications,Image comparison,Binary image,Baddeley's Delta Metric,Distance transform,Generalized distance transform,HAUSDORFF DISTANCE,EDGE,ALGORITHM,IMAGES,RECOGNITION,COMPUTATION}},
  language     = {{eng}},
  pages        = {{479--495}},
  title        = {{On the role of distance transformations in Baddeley’s Delta Metric}},
  url          = {{http://doi.org/10.1016/j.ins.2021.05.034}},
  volume       = {{569}},
  year         = {{2021}},
}
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