Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/1859
Title: | Automatic Calibration Marker Detection for Radiography Images | Authors: | Novovic L. Ostojić, Vladimir Starcevic D. Petrović, Višnja |
Issue Date: | 1-Jan-2018 | Journal: | 2018 26th Telecommunications Forum, TELFOR 2018 - Proceedings | Abstract: | © 2018 IEEE. In this paper we analyse the possibility of simple detection of circular radiography markers. To detect the marker, we utilised the Hough transform. Two approaches were analysed: with detecting image edges and without image edge detection where pixel gradient was used in Hough voting process, i.e. to increase the accumulator values. Approaches were evaluated on 13 clinical radiography images. It was shown that approach that detects image edges spatially matches the reference circles only 0.22 % less than manual annotation values, whereas approach that uses just the gradient magnitudes spatially matches the reference circles 3.2 % less than manual annotations. | URI: | https://open.uns.ac.rs/handle/123456789/1859 | ISBN: | 9781538671702 | DOI: | 10.1109/TELFOR.2018.8611868 |
Appears in Collections: | FTN Publikacije/Publications |
Show full item record
SCOPUSTM
Citations
1
checked on May 3, 2024
Page view(s)
15
Last Week
4
4
Last month
0
0
checked on May 10, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.