Abstract
The anthracnose is one of the most serious diseases in the growth period of mango. In order to take preventive measures timely, it is indispensable to calculate accurate statistics on the distribution density of anthrax spores on the farm, which has challenges in accurate instance segmentation of adherent spores. Based on the traditional watershed algorithm, which treats the image as a morphological topography and segments the image by finding the lowest and highest points on the topography, we proposed the marked watershed algorithm combined with morphological preprocessing to realize the segmentation of adherent spores. Firstly, the spore images are preprocessed with morphology technique. Then the gradient values of the spore images are calculated. The segmentation of spores is performed in the gradient image by the watershed algorithm with foreground mark and background mark. The experimental result shows that our proposal has a better segmentation performance for adherent spores than the morphological method and the level set evolution.
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Acknowledgements
This research was supported by Hainan Province Natural Science Foundation, China (619QN195, 618QN218), the National Natural Science Foundation of China (61963012), Key R&D Project of Hainan Province, China (ZDYF2018015), and Collaborative Innovation Fund Project of Tianjin University-Hainan University (HDTDU201907).
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Wang, J. et al. (2020). Marked Watershed Algorithm Combined with Morphological Preprocessing Based Segmentation of Adherent Spores. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_157
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DOI: https://doi.org/10.1007/978-981-13-9409-6_157
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