Turfgrass quality can be measured based on a percent green value. Images collected in a lightbox may contain part of the lightbox and needs to be removed in a percent green calculation. Image calculations done on the HSV scale.
This project replaces Fiji/ImageJ macros, exporting a time-series dataset of repetitive blocks to a pandas dataframe for further analysis.
- Python 3.7
Contact me at my profile email if you need some edits for your folder structure. My script follows a vary naive approach.
- Zhang, C., G. D. Pinnix, Z. Zhang, G. L. Miller, and T. W. Rufty. 2017. Evaluation of Key Methodology for Digital Image Analysis of Turfgrass Color Using Open-Source Software. Crop Sci. 57:550-558. doi:10.2135/cropsci2016.04.0285
- North Carolina State University's Turfgrass DIA ImageJ plugin
- Karcher, D. E., and M. D. Richardson. 2003. Quantifying Turfgrass Color Using Digital Image Analysis. Crop Sci. 43:943-951. doi:10.2135/cropsci2003.9430
- Image analysis tools for turfgrass managers and scientists by Garett Heineck
- Reiter, M., J. Friell, B. Horgan, D. Soldat, and E. Watkins. 2017. Drought Response of Fine Fescue Mixtures Maintained as a Golf Course Fairway. International Turfgrass Society Research Journal 13:65-74. doi:10.2134/itsrj2016.06.0460