blob detection and dust removal

[Vighnesh Birodkar]

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 
> <javascript:>> 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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