[BioC] EBImage crop failure

[Wolfgang Huber]

Dear Michael

Michael Cole scripsit 09/02/2011 06:22 PM:
> Thanks Gregoire,
>
> The images are color. Can I assume img[1:200, 1:200,x] gives a cropped
> image in red,blue,green where x={1,2,3}?

Yes.
What do you get when you type

(a <- readImage("xxxxxxxx"))

	Wolfgang


> Michael
>
>
> On Fri, Sep 2, 2011 at 3:10 AM, Gregoire Pau<gregoire.pau at embl.de>  wrote:
>> Hello Michael,
>>
>> EBImage represents images as multidimensional arrays. Color images are
>> usually represented as 3-dimensional ones, where the third dimension
>> contains the color components.
>>
>>  From your example, it seems that are you are manipulating 3-dimensional
>> arrays, explaining why "a[1:120,50:120]" fails. Use "a[1:120,50:120,]"
>> instead to crop images.
>>
>> Is the image you are working with is a grayscale one ? In this case, you
>> are maybe manipulating an image that was stored as a color one,
>> explaining your array has 3 dimensions. Doing "a = Image(a[,,1],
>> color=Grayscale)" will fix this.
>>
>> Hope this helps,
>> Cheers,
>>
>> Greg
>> ---
>> Gregoire Pau
>> EMBL Research officer
>> http://www.embl.de/~gpau/
>>
>> On 28/08/2011 15:22, Michael Cole wrote:
>>> Using the latest version of EBImage and ver 8:6.6.9.7-5 of ImageMagick (debian
>>> package) several EBImage operations fail.
>>>
>>> In particular, cropping an image with:
>>> a<-readImage("xxxxxxxx")
>>> a[1:120,50:120] # fails with "incorrect number of dimensions"]
>>>
>>> I can get cropped images by doing:
>>> a[1:120,50:120,1] # display gives correct region with a red mask
>>> a[1:120,50:120,c(1,0,0)] # display gives correct region with a red mask
>>> a[1:120,50:120,c(1,0,1)] # display gives correct region with a yellow mask
>>> a[1:120,50:120,c(1,1,1)] # display gives correct region as grayscale
>>> a[1:120,50:120,c(0,1,1)] # display gives correct region with a yellow mask
>>>
>>> and so on.
>>>
>>> Has there been a change in EBImage that is not reflected in the documentation?
>>>
>>> I am trying to build histograms for each color channel to build classification
>>> models.
>>>
>>>
>>> Thanks,
>>>
>>> Michael
>>>
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>>
>
>
>


-- 


Wolfgang Huber
EMBL
http://www.embl.de/research/units/genome_biology/huber