Publication detail

Tuning of grayscale computer vision systems

ŠKRABÁNEK, P. MARTÍNKOVÁ, N.

Original Title

Tuning of grayscale computer vision systems

Type

journal article in Web of Science

Language

English

Original Abstract

Computer vision systems perform based on their design and parameter setting. In computer vision systems that use grayscale conversion, the conversion of RGB images to a grayscale format influences performance of the systems in terms of both results quality and computational costs. Appropriate setting of the weights for the weighted means grayscale conversion, co-estimated with other parameters used in the computer vision system, helps to approach the desired performance of a system or its subsystem at the cost of a negligible or no increase in its time-complexity. However, parameter space of the system and subsystem as extended by the grayscale conversion weights can contain substandard settings. These settings show strong sensitivity of the system and subsystem to small changes in the distribution of data in a color space of the processed images. We developed a methodology for Tuning of the Grayscale computer Vision systems (TGV) that exploits the advantages while compensating for the disadvantages of the weighted means grayscale conversion. We show that the TGV tuning improves computer vision system performance by up to 16% in the tested case studies. The methodology provides a universally applicable solution that merges the utility of a fine-tuned computer vision system with the robustness of its performance against variable input data.

Keywords

Computer vision; Parameter optimization; Performance evaluation; WECIA graph; Weighted means grayscale conversion

Authors

ŠKRABÁNEK, P.; MARTÍNKOVÁ, N.

Released

17. 8. 2022

Publisher

ELSEVIER

Location

AMSTERDAM

ISBN

0141-9382

Periodical

DISPLAYS

Number

74

State

Kingdom of the Netherlands

Pages from

102286

Pages to

102286

Pages count

9

URL

https://www.sciencedirect.com/science/article/pii/S0141938222001044

BibTex

@article{BUT179012,
  author="Pavel {Škrabánek} and Natália {Martínková}",
  title="Tuning of grayscale computer vision systems",
  journal="DISPLAYS",
  year="2022",
  number="74",
  pages="102286--102286",
  doi="10.1016/j.displa.2022.102286",
  issn="0141-9382",
  url="https://www.sciencedirect.com/science/article/pii/S0141938222001044"
}