Tuning of grayscale computer vision systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081766%3A_____%2F22%3A00560958" target="_blank" >RIV/68081766:_____/22:00560958 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216305:26210/22:PU145434 RIV/00216224:14310/22:00126692

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0141938222001044?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0141938222001044?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.displa.2022.102286" target="_blank" >10.1016/j.displa.2022.102286</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Tuning of grayscale computer vision systems

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Tuning of grayscale computer vision systems

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Displays

ISSN

0141-9382

e-ISSN

1872-7387

Svazek periodika

74

Číslo periodika v rámci svazku

September

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

9

Strana od-do

102286

Kód UT WoS článku

000848013000002

EID výsledku v databázi Scopus

2-s2.0-85136309947