Template matching is an algorithm that can be used for object-detections in images.
The algorithm computes the probability to find one (or several) template images provided by the user into a larger image.
For more theoretical details, see the section Template Matching : How does it work ?.
You can find a similar implementation in KNIME in this repo.
If you use this implementation for your research, please cite:
Multi-Template Matching: a versatile tool for object-localization in microscopy images;
Laurent SV Thomas, Jochen Gehrig
bioRxiv 619338; doi: https://doi.org/10.1101/619338
This plugin is using OpenCV in Fiji thanks to IJ-OpenCV.
see also:
Domínguez, César, Jónathan Heras, and Vico Pascual. "IJ-OpenCV: Combining ImageJ and OpenCV for processing images in biomedicine." Computers in biology and medicine 84 (2017): 189-194.
We also distribute a python package available on PyPI.
The content of this wiki (including illustrations and videos) is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
As a derived work of IJ-OpenCV, the source codes are licensed under GPL-3.
This work has been part of the PhD project of Laurent Thomas under supervision of Dr. Jochen Gehrig at:
ACQUIFER a division of DITABIS AG
Digital Biomedical Imaging Systems AG
Freiburger Str. 3
75179 Pforzheim
This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 721537 ImageInLife.
Image courtesy Jakob Gierten (COS, Heidelberg)
Dataset available on Zenodo