How to Eliminate False Positives detected in Segmentation?

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Tarcisio Lima
Tarcisio Lima 2018-6-5
编辑： Tarcisio Lima 2018-6-11

I am developing in MATLAB a code, which is supposed to identify the area on a leaf that contains spots to report the severity of a disease.

During my research, I found out about LeafSnap and got inspired by it. So, I tried to follow the paper to segment the leaf on the image using OpenCV Expectation Maximization, which is trained using S and V form HSV color space; however, it still returns some false positives due to reflection or shadow.

As you can see above, the color space have yellowish (in direct sunlight) or blueish (in shadow).

Please suggest any way by which I can avoid that false positives! Thank you

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Image Analyst
Image Analyst 2018-6-6
Try the attached demo. It works for the one image you uploaded but may not work well with those fixed thresholds depending on how green and cluttered your "background" is.
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Image Analyst
Image Analyst 2018-6-10
If this is people in the wild, like the general public who are uploading to your web site, then you may have to use deep learning. Otherwise, if they're research partners of yours, instruct them with tips on how to take a good photo.
Tarcisio Lima
Tarcisio Lima 2018-6-11
编辑：Tarcisio Lima 2018-6-11
I will take a look in deep learning and see if it can solve the issue. Thank you!

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