How do you plan to find the position of the real crystals ? Maybe the function you will use to find the original crystals will take a mask argument ? On Mon, May 2, 2016 at 1:07 AM, Raphael Okoye <raphael@aims.ac.za> wrote:

hi Vighnesh,

Further processing involves getting the size and positions of real crystals (I want to use the positions to estimate the pair correlation function and then using the pair correlation function to estimate the structure factor) The image comes from a sequence of time lapse images. There are dust particles of various sizes in the images so if they are not eliminated, a false structure factor will be determined. The median filter took care of the very little ones but didn’t work for the bigger ones.

Thanks a lot.

Raphael

On 1 May 2016 at 21:27, Vighnesh Birodkar <vighneshbirodkar@gmail.com> wrote:

...

Hi

That really depends on your application. What's your motivation for removing these dust particles ? How are these images going to be processed further ?

Thanks Vighnesh

On Monday, May 2, 2016 at 12:13:27 AM UTC-4, Raphael wrote:

...

hi Vighnesh,

Thanks a bunch!! I see my error now.

Actually that blob you detected a dust particle. Which operation would you suggest to erase it? I tried morphological erosion but it doesn't take it away.

Thanks Raphael

On 1 May 2016 at 18:27, Vighnesh Birodkar <vighnesh...@gmail.com> wrote:

...

Hello Raphael

The error here is because the output of blob_doh in a numpy array of blobs, it is not an image meant for display. If you notice the example the blobs are being drawn separately inside the for loop. If no blobs are being detected, you can adjust the threshold. Lowering the threshold will make the function detect more blobs. It is clarified futher in the documentation

http://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.bl...

I was able to detect one blob in your image with the default threshold value. See:

https://gist.github.com/vighneshbirodkar/c16515126e648cf92f08d3319d3a023e

Find the result attached.

Thanks Vighnesh

On Saturday, April 30, 2016 at 2:02:51 AM UTC-4, Raphael wrote:

...

hi folks,

Got a problem removing dust and identifying blobs/crytals. Kindly see my code below

from __future__ import division, print_function import matplotlib.pyplot as plt import numpy as np from skimage import io, feature, color, measure, draw, img_as_float, exposure from skimage.filters.rank import median from skimage.feature import blob_dog, blob_log, blob_doh from skimage.morphology import disk

#raw image image_raw = img_as_float((io.imread('/home/raphael/Documents/ScikitImage/Run 4-2_00061cropped.tif'))) (RawImage.tif attached) plt.imshow(image_raw)

#converted to grayscale

img_gray = color.rgb2gray(io.imread('/home/raphael/Documents/ScikitImage/Run 4-2_00061cropped.tif')) plt.imshow(image_gray)

#applied median filter to take out small dust particles. But the big dust particle on the top right corner still persists (see median1.png attached) img_filtered=median(img_gray,disk(10)) plt.imshow(img_filtered)

#applied adapthist to make image more clearer (see adaptive.png)

img_equalized=exposure.equalize_adapthist(img_filtered) plt.imshow(img_equalized)

#trying to detect the crystals/blobs. I followed the example here http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_blob.... But this gave an error. matplotlib was not happy with the data type blobs_doh = blob_doh(img_equalized, max_sigma=30, threshold=.1) plt.imshow(blobs_doh)

My problems are:

1. I could not get the dust particle out especially the really big one on the top right. How can I get it out?

2. I could not detect the crystals/blobs in the image using blob_doh

Any ideas/suggestions is highly appreciated. Thank you!

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