skimage.feature

[Zsuzsanna Püspöki]

Thanks for your message. 

Yes, I have tried both. I can detect all the blobs, but somehow the 
algorithm does not capture the size perfectly. I am wondering why there is 
such a difference.
Actually, my intention is to use the results provided by this python code 
to make a comparison on real data between different algorithms (including 
mine). But I am not very convinced by those detections, since they do not 
meet with what I expect. 

Regards,

Zsuzsanna

2015. május 28., csütörtök 11:15:09 UTC+2 időpontban Kai Wiechen a 
következőt írta:
>
> Have you tried to modify the overlap or the max_sigma parameters? There is 
> an internal function _prune_blobs to remove overlapping signals favoring 
> larger ones.
>
> Regards,
>
> Kai
>
>
>
> Am Donnerstag, 28. Mai 2015 08:35:08 UTC+2 schrieb Zsuzsanna Püspöki:
>>
>> I am trying to use the blob_dog, blob_log, blob_doh from skimage.feature 
>> on some synthetic data.
>>
>> 1. Why do you obtain such different results for the LoG and DoG on your 
>> sample data: 
>> http://scikit-image.org/docs/dev/auto_examples/plot_blob.html 
>> <https://ewa.epfl.ch/owa/redir.aspx?C=9lxjKPMqzkiQgZDrW5vS3JnRU_KdbNII73D0phYBj9Do6bHbjT_Oecmyv0YkaA_xkC-zzPeoTjQ.&URL=http%3a%2f%2fscikit-image.org%2fdocs%2fdev%2fauto_examples%2fplot_blob.html> 
>> ? 
>> I would expect something very similar.  
>>
>> 2. I am running the following line on the attached image: blobs_log = 
>> blob_log(image_gray, overlap = 0, min_sigma=3, max_sigma=25, num_sigma=100, 
>> threshold=.1)
>>
>> I cannot arrive to detect precisely the size of the bigger spots (though 
>> the range I put is enough, hence the huge spot). The increase in num_sigma 
>> does not solve the issue. I would expect perfect results here.  
>>
>> 3. Is there an easy way to visualize the N best detections?
>>
>>
>>
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