Automated framework for accurate segmentation of leaf images for plant health assessment-Reference-Cited by-同舟云学术

Automated framework for accurate segmentation of leaf images for plant health assessment

Published:2019-07-12 Issue:8 Volume:191 Page:
ISSN:0167-6369
Container-title:Environmental Monitoring and Assessment
language:en
Short-container-title:Environ Monit Assess

Author:

Ghazal Mohammed^ORCID,Mahmoud Ali,Shalaby Ahmed,El-Baz Ayman

Funder

Office of Research and Sponsored Programs of Abu Dhabi University

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s10661-019-7615-9.pdf

Reference33 articles.

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2. Barbedo, J.G.A. (2017). A new automatic method for disease symptom segmentation in digital photographs of plant leaves. European Journal of Plant Pathology, 147(2), 349–364.

3. Bauer, S, Korc, F, Förstner, W. (2009). Investigation into the classification of diseases of sugar beet leaves using multispectral images. In E.J. van Henten, D. Goense, C. Lokhorst (Eds.) Precision agriculture (Vol. 9, pp. 229– 238).

4. Besag, J. (1986). On the statistical analysis of dirty pictures. Journal of the Royal Statistical Society Series B (Methodological), 48(3), 259–302.

5. Bouman, C, & Sauer, K. (1993). A generalized gaussian image model for edge-preserving map estimation. IEEE Transactions on Image Processing, 2(3), 296–310.

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