Sub-pixel X-marker detection by Hough transform
| Autor: | Farshid Karimi, Saeed Solouki, Hamid Soltanian-Zadeh, Hojjat Aalizadeh, Ali Yazdani |
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| Rok vydání: | 2018 |
| Předmět: |
Pixel
Computer science business.industry Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition 02 engineering and technology Filter (signal processing) 01 natural sciences Thresholding Hough transform law.invention Image (mathematics) law 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Calibration 020201 artificial intelligence & image processing Artificial intelligence 010306 general physics business Camera resectioning |
| Zdroj: | 2018 25th National and 3rd International Iranian Conference on Biomedical Engineering (ICBME). |
| DOI: | 10.1109/icbme.2018.8703591 |
| Popis: | High precision center detection of X-markers is required in many applications such as navigation surgery systems and camera calibration. Hough transform is a preferable tool for extracting intersecting lines in an image, which leads to center detection. In this paper, we detect X-marker centers by the sub-pixel precision, using Hough transform. Switching to Hough space helps us to apply processes like thresholding, filtering and weighted averaging on coordinates. The algorithm involves two parameters ‘Hough Size’ and ‘Filter Size’ required to be adjusted for best performance of the algorithm. A dataset of 900 images is used and best performance is achieved by values of 180 and 23 for the above parameters, respectively. Using this setting, 90.8% of the centers are detected successfully by the sub-pixel precision. The average distance between detected centers and reference centers is 0.51 pixels. This suggests that the proposed algorithm has the potential to be utilized for sub-pixel marker detection. |
| Databáze: | OpenAIRE |
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