Description of the problem
A number of diseases can be identified from fundus. ...
Typical macular diseases that may be able to solve machine vision
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Finally we want to detect blood vessels and some dot area clearly. So it is necessary to create masks. I show original image in (Fig.3.1). I tried to use HSV images of retina images and I detected black area that is not retina images. -(Fig.3.2) And I also make mask to detect not blood vessel area. -(Fig.3.3) This area includes some dot and leaser reflection area. And I tried to make leaser reflection area mask. But it is not so good. -(Fig.3.4) We have to try some other filter to crate this mask.
Fig.3.1 Original Image of Retina Fig.3.2 Mask of Black Area
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Next I tried to make binary image to use green channel image. I showed binary images these are different thresholds. Showed in Fig3.7 (a) and Fig3.7 (b).
Fig 3.7 (a) Green channel binary Fig 3.7 (b) Green channel binary
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Image is close to what it’s required to be, but not enough to be able to use it. So I tried to other method. I use dividual threshold. I used 21- neighbor and 31-neighbor. Then I crated binary images use these neighbor. I showed 31-neighbor binary image in Fig3.8 (a) and 21-neighbor binary image in Fig3.8 (b).
Fig3.8 (a) 21-neighbor binary image Fig3.8 (b) 31-neighbor binary image
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These images are better than Fig3.7. But it is still noisy. So I used expansion and contraction 3 times. I showed these images Fig3.9 (a) and Fig3.9 (b).
Fig3.9 (a) 31-neighbor Fig3.9 (b) 21-neighbor
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