How about labeling manually a dataset for training, then let machine learning do the rest (of course local binary pattern could be used as feature)?
By labeling, I mean for each image draw the region where there are grass, and the region where there are cover. On Mon, Nov 6, 2017 at 4:15 AM, Zhenjiang Zhou <zhenjiang.z...@slu.se> wrote: > Hi there, > > I am new python user, trying to use python to solve a question in my > research, which is simple but not easy question: > > > > The attached image is mixture of two plants: grass and clover, grass is > the one with long leaf, clover is the one with round leaf. > > So they have different shape, but very similar color > > > > So the question is how to use python to estimate the percentage of each > plant in the whole image (%) > > > > From the literature, local binary pattern might be used, but I am not so > sure it can do good job here. > > Any help is highly appreciated, I can say that this question is a big > issue in my research area. > > Looking forwards to your reply. > > > > Zhenjiang Zhou > > Postdoc > > *Swedish University of Agricultural Sciences* > > Department of Agricultural Research for Northern Sweden > 901 83 UMEÅ > Sweden > Visiting address: Skogsmarksgränd > Phone:+46 90-786 8731 <+46%2090%20786%2087%2031> > > *zhenjiang.z...@slu.se <zhenjiang.z...@slu.se> *[image: > slu-logo-rgb-web-medium] > > > > _______________________________________________ > scikit-image mailing list > scikit-image@python.org > https://mail.python.org/mailman/listinfo/scikit-image > > -- *Dzung Nguyen* PhD Student Electrical Engineering and Computer Science, Northwestern University, IL, USA http://users.eecs.northwestern.edu/~dtn419/
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