blob detection and dust removal

Tue May 3 00:48:01 EDT 2016

hi Vighnesh,

Thats an interesting question..never really given it a thought. I think
this http://scikit-image.org/docs/dev/auto_examples/plot_label.html or the
help in section  3.3.4.1.2 given here
http://www.scipy-lectures.org/packages/scikit-image/ might work. As how to
create the mask image to mask dust particles, I'm currently not sure how to
implement that in scikit image.

Thanks a lot.
3.3.4.1.2

On 2 May 2016 at 13:54, Vighnesh Birodkar <vighneshbirodkar at gmail.com>
wrote:

> regionprops takes a labelled image as input. The question still remains,
> how will you generate the image in which the interested regions are
> labelled accordingly. You need to make that part of your algorithm exclude
> the dust particles.
>
> On Mon, May 2, 2016 at 3:34 PM, Raphael Okoye <raphael at aims.ac.za> wrote:
>
>> hi Vighnesh
>>
>> I plan to use this guy
>> http://scikit-image.org/docs/dev/auto_examples/plot_regionprops.html.
>> The documentation  on regionprops (
>> http://scikit-image.org/docs/dev/api/skimage.measure.html#regionprops)
>> says I can get parameters such as co-ordinate positions, equivalent
>> diameter etc
>>
>>  But first I need to think of a way to exclude the dust particles, that
>> is the main challenge.
>>
>> Thanks
>> Raphael
>>
>> On 2 May 2016 at 02:30, Vighnesh Birodkar <vighneshbirodkar at gmail.com>
>> wrote:
>>
>>> 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 at 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 at 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... at 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.blob_doh
>>>>>>>
>>>>>>> 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.html
>>>>>>>> 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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