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https://doi.org/10.17559/TV-20160224214607

Real-Time Automatic Colour Calibration for NAO Humanoids

Anastasia Bolotnikova ; iCV Research Lab, University of Tartu, Institute of Technology, Nooruse 1, 50411 Tartu, Estonia
Gholamreza Anbarjafari   ORCID icon orcid.org/0000-0001-8460-5717 ; iCV Research Lab, University of Tartu, Institute of Technology, Nooruse 1, 50411 Tartu, Estonia

Puni tekst: engleski, pdf (1 MB) str. 957-961 preuzimanja: 301* citiraj
APA 6th Edition
Bolotnikova, A. i Anbarjafari, G. (2018). Real-Time Automatic Colour Calibration for NAO Humanoids. Tehnički vjesnik, 25 (4), 957-961. https://doi.org/10.17559/TV-20160224214607
MLA 8th Edition
Bolotnikova, Anastasia i Gholamreza Anbarjafari. "Real-Time Automatic Colour Calibration for NAO Humanoids." Tehnički vjesnik, vol. 25, br. 4, 2018, str. 957-961. https://doi.org/10.17559/TV-20160224214607. Citirano 19.11.2019.
Chicago 17th Edition
Bolotnikova, Anastasia i Gholamreza Anbarjafari. "Real-Time Automatic Colour Calibration for NAO Humanoids." Tehnički vjesnik 25, br. 4 (2018): 957-961. https://doi.org/10.17559/TV-20160224214607
Harvard
Bolotnikova, A., i Anbarjafari, G. (2018). 'Real-Time Automatic Colour Calibration for NAO Humanoids', Tehnički vjesnik, 25(4), str. 957-961. https://doi.org/10.17559/TV-20160224214607
Vancouver
Bolotnikova A, Anbarjafari G. Real-Time Automatic Colour Calibration for NAO Humanoids. Tehnički vjesnik [Internet]. 2018 [pristupljeno 19.11.2019.];25(4):957-961. https://doi.org/10.17559/TV-20160224214607
IEEE
A. Bolotnikova i G. Anbarjafari, "Real-Time Automatic Colour Calibration for NAO Humanoids", Tehnički vjesnik, vol.25, br. 4, str. 957-961, 2018. [Online]. https://doi.org/10.17559/TV-20160224214607

Sažetak
A challenge in NAO soccer robots is colour calibration. Good colour calibration can result in robust and accurate self-localization of the robot. Currently manual calibration is the only solution, which is used. In this paper, we are proposing an automatic real-time, accurate YUV colour space based colour calibration technique. In order to define average values for the desired colour classes namely orange, white, green and purple, a specified set of frames from the NAO camera are analysed. These average values are corrected by luminance analysis of a new frame and are passed to the K-means clustering algorithm as a set of initial means. In addition to these four values, a set of initial means of the K-means algorithm contains 16 values that are calculated in the following manner: the frame being processed is divided into 4 by 4 grids and the average value from every grid serves as an initial mean for K-means clustering. Consequently, colours of a similar type are combined into clusters. The final step of the proposed technique is cluster classification in which the average values of the desired colour classes are corrected by luminance analysis. As NAO cameras provide video streams in YUV format and the proposed algorithm uses this format there is no need for additional computational steps for conversation between the colour spaces. As a result, computational process is reduced compared to current techniques.

Ključne riječi
automatic colour calibration; K-means clustering; localisation; NAO Robots; RoboCup

Hrčak ID: 204438

URI
https://hrcak.srce.hr/204438

Posjeta: 550 *