I was thinking about closing too, but a little bit slower than Markus,
show =: (-.&' ')"1 @: ":
expand =: 3 : '(,.~{."1)(,.{:"1)(,~{.)(,{:) y'
minf =: 3 : '3 3 <./@:, ;. _3 expand y'
maxf =: 3 : '3 3 >./@:, ;. _3 expand y'
(show im1);show minf maxf im1
+--------------------------+--------------------------+
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000100000000000|00000000000000100000000000|
|00000000000001110000000000|00000000000001110000000000|
|00000000000001110000000000|00000000000001110000000000|
|00000000000011111000000000|00000000000011111000000000|
|00000000000111111100000000|00000000000111111100000000|
|00000000000111101100000000|00000000000111111100000000|
|00000000001111111110000000|00000000001111111110000000|
|00000000011111111100000000|00000000011111111110000000|
|00000000111111111111100000|00000000111111111111100000|
|00000001111111111111010000|00000001111111111111110000|
|00000011111111111111010000|00000011111111111111110000|
|00000101111111111110011100|00000111111111111111111100|
|00001111011110110101011100|00001111111111111111111100|
|00000111111111111111110000|00000111111111111111110000|
|00000011110011100101100000|00000011111111111111100000|
|00000001111111111101100000|00000001111111111111100000|
|00000001111111110100000000|00000001111111111110000000|
|00000000011111110110000000|00000000011111111110000000|
|00000000010101010000000000|00000000011111111000000000|
|00000000000010110000000000|00000000000111111000000000|
|00000000000110111000000000|00000000000111111000000000|
|00000000000110110000000000|00000000000111110000000000|
|00000000000010100000000000|00000000000011100000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
+--------------------------+--------------------------+
Greetings,
Ben
________________________________________
From: Programming [programming-boun...@forums.jsoftware.com] on behalf of
Schmidt-Gröttrup, Markus [m.schmidt-groett...@hs-osnabrueck.de]
Sent: Tuesday, June 27, 2017 13:38
To: programm...@jsoftware.com
Subject: Re: [Jprogramming] cleanest diamond
A morphological closure is the reasonable treating.
With these definitions:
im1 =: _48+ (, ;._2) a. i. 0 : 0
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
00000000000000100000000000
00000000000001110000000000
00000000000001110000000000
00000000000011111000000000
00000000000111111100000000
00000000000111101100000000
00000000001111111110000000
00000000011111111100000000
00000000111111111111100000
00000001111111111111010000
00000011111111111111010000
00000101111111111110011100
00001111011110110101011100
00000111111111111111110000
00000011110011100101100000
00000001111111111101100000
00000001111111110100000000
00000000011111110110000000
00000000010101010000000000
00000000000010110000000000
00000000000110111000000000
00000000000110110000000000
00000000000010100000000000
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
) show =: (-.&' ')"1 @: ":
expand =: 3 : '(,.~{."1)(,.{:"1)(,~{.)(,{:) y'
minf =: 3 : '3 3 <./@:, ;. _3 expand y'
maxf =: 3 : '3 3 >./@:, ;. _3 expand y'
(show im1);show minf maxf im1
+--------------------------+--------------------------+
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000100000000000|00000000000000100000000000|
|00000000000001110000000000|00000000000001110000000000|
|00000000000001110000000000|00000000000001110000000000|
|00000000000011111000000000|00000000000011111000000000|
|00000000000111111100000000|00000000000111111100000000|
|00000000000111101100000000|00000000000111111100000000|
|00000000001111111110000000|00000000001111111110000000|
|00000000011111111100000000|00000000011111111110000000|
|00000000111111111111100000|00000000111111111111100000|
|00000001111111111111010000|00000001111111111111110000|
|00000011111111111111010000|00000011111111111111110000|
|00000101111111111110011100|00000111111111111111111100|
|00001111011110110101011100|00001111111111111111111100|
|00000111111111111111110000|00000111111111111111110000|
|00000011110011100101100000|00000011111111111111100000|
|00000001111111111101100000|00000001111111111111100000|
|00000001111111110100000000|00000001111111111110000000|
|00000000011111110110000000|00000000011111111110000000|
|00000000010101010000000000|00000000011111111000000000|
|00000000000010110000000000|00000000000111111000000000|
|00000000000110111000000000|00000000000111111000000000|
|00000000000110110000000000|00000000000111110000000000|
|00000000000010100000000000|00000000000011100000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
|00000000000000000000000000|00000000000000000000000000|
+--------------------------+--------------------------+
ushift =: 0 ,~ }.
dshift =: 0 , }:
lshift =: 0 ,"1~ }."1
rshift =: 0 ,"1 }:"1
ulshift =: ushift@lshift
urshift =: ushift@rshift
dlshift =: dshift@lshift
drshift =: dshift@rshift
clos22 =: (]*.rshift)@:(]*.dshift)@:(]+.lshift)@:(]+.ushift)
closc4 =:
(]*.urshift)@:(]*.drshift)@:(]*.rshift)@:(]*.dshift)@:(]+.dlshift)@:(]+.ulshift)@:(]+.lshift)@:(]+.ushift)
show =: (-.&' ')"1 @: ":
closures with a 2*2 square or a circle with diameter 4 are shown with:
show im1 + clos22 im1
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
00000000000000200000000000
00000000000002220000000000
00000000000002220000000000
00000000000022222000000000
00000000000222222200000000
00000000000222212200000000
00000000002222222220000000
00000000022222222210000000
00000000222222222222200000
00000002222222222222120000
00000022222222222222120000
00000212222222222221122200
00002222122221221212122200
00000222222222222222220000
00000022221122211212200000
00000002222222222212200000
00000002222222221210000000
00000000022222221220000000
00000000021212120000000000
00000000000121220000000000
00000000000221222000000000
00000000000221220000000000
00000000000021200000000000
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
show im1 + closc4 im1
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
00000000000000200000000000
00000000000002220000000000
00000000000002220000000000
00000000000022222000000000
00000000000222222200000000
00000000000222212200000000
00000000002222222220000000
00000000022222222211000000
00000000222222222222200000
00000002222222222222120000
00000022222222222222121000
00000212222222222221122200
00002222122221221212122200
00000222222222222222220000
00000022221122211212200000
00000002222222222212200000
00000002222222221211000000
00000000122222221220000000
00000000021212121100000000
00000000001121221000000000
00000000000221222000000000
00000000000221220000000000
00000000000021200000000000
00000000000000000000000000
00000000000000000000000000
00000000000000000000000000
Best regards,
Markus
-----Ursprüngliche Nachricht-----
Von: Programming [mailto:programming-boun...@forums.jsoftware.com] Im Auftrag
von Marshall Lochbaum
Gesendet: Dienstag, 27. Juni 2017 10:20
An: programm...@jsoftware.com
Betreff: Re: [Jprogramming] cleanest diamond
A common strategy that may work for you is just to ignore the spacial data and
perform some sort of clustering (like k-means, with k=2) on the intensities.
Then classify pixels according to which cluster they fall in.
An approach that does use this data, and which I expect would be much slower
but somewhat more accurate, would be to use the realization that a threshold
that maximizes the number of contiguous 1's minimizes the number of adjacent
pixels which are separated by the threshold (that is, adjacent 0-1 pairs). To
minimize this number, we need to collect all pairs of adjacent pixels, then
turn consider these pairs as intervals and compute for each possible threshold
the number of these intervals which contain it.
I don't have any particularly clever ways to find pairs of adjacent pixels. For
the strictest form of adjacency, with no diagonals, the verb ((}. ,.&, }:) ,
(}."1 ,.&, }:"1)) will get them all. Each pair should then be sorted, to put
them in a standard interval form.
An efficient way to turn a list of intervals into a list of
number-of-intervals-containing uses an obverse of monad (I.), which I am
increasingly coming to believe is a major feature missing from J. To
wit:
x =. 4 7 2 4 1 7 8
(10$0) (#/.~@])`(~.@])`[}"1 x
0 1 1 0 2 0 0 2 1 0
I. (10$0) (#/.~@])`(~.@])`[}"1 x
1 2 4 4 7 7 8
(/:~x) -: I. (10$0) (#/.~@])`(~.@])`[}"1 x
1
The verb ((#/.~@])`(~.@])`[}) with an appropriate left argument is an left
inverse to I. ignoring trailing zeros, and a right inverse to I.
ignoring ordering. It counts, for each number in (i.n) where n is the length of
the left argument, how many elements on the right are equal to it. To get our
interval count, we just take this count for the starts of intervals, subtract
the counts for ends of intervals, and do a running
sum:
]a =. /:~"1 ]10 2?@$10 NB. intervals obtained from image
3 4
5 9
5 7
0 6
0 5
3 6
3 6
1 7
2 9
1 4
+/\ -/ (10$0) (#/.~@])`(~.@])`[}"1 |:a
2 4 5 8 6 7 4 2 2 0
The above example for n=10 has counts increasing then falling, but if the
values in the image are clustered like yours are, then they should dip in the
middle. Just picking the minimum won't work, because a threshold of 0 or 256
trivially maximizes contiguous 0's or 1's.
However, it should be possibly to either penalize values at the edges (say, by
adding a multiple of (*:128-~i.256) or select a local minimum near the middle
to obtain a threshold.
One other note is that performing a morphological closure on the ones will
remove any small gaps left by thresholding while preserving the diamond shape.
Marshall
On Mon, Jun 26, 2017 at 05:54:44PM -0400, Brian Schott wrote:
> In my webcam playing-card image recognizer, I am trying to set a
> threshold that depends on the amount of ambient lighting on the
> playing cards. If the threshold is set well than I can better
> distinguish between the card suits and pips. The threshold is a number
> between 0 and 255 and my experience has seen it between 100 and 180.
> But I have no algorithm to get a best value, only an eyeballed acceptable
> value.
>
> My idea is to present the webcam with any card with the diamond suit
> and to search for a threshold value that produces the best diamond
> (during the setup period of the app usage, and then to leave the
> threshold value alone later).
>
> The image is always inside a boolean array of shape 30 26. The center
> of the array always is inside the diamond image but that's about the
> only known fact, because the image can be off-center slightly and even
> tilted slightly and the size of the diamond in the image is unknown.
> If the threshold is set too high the boolean image is all 1s, if the
> threshold is set too low, the boolean image is all 0s. (The diamond
> suit is easiest to use because of its relatively regular shape on
> almost any card deck.)
>
> The two examples below are meant to show a dirty diamond and a very
> clean diamond. The clean example has no holes of 0s internal to the
> external perimeter of the diamond. I cannot guarantee that every image
> can be captured with a perfectly clean diamond, so I would sort of
> like to find the threshold that produces the diamond with the greatest
> number of contiguous 1's, sort of. I feel as if there is likely to be
> a gradual increase in the number of contiguous 1's in the sweetspot
> range of the threshold value, but I'm not sure of this.
>
> I am open to other ideas for accomplishing this thresholding, btw. But
> mostly I am looking for J code ideas.
>
> You may be able to copy and paste each example from this email. I
> suppose I could
>
> 00000000000000000000000000
> 00000000000000000000000000
> 00000000000000000000000000
> 00000000000000000000000000
> 00000000000000100000000000
> 00000000000001110000000000
> 00000000000001110000000000
> 00000000000011111000000000
> 00000000000111111100000000
> 00000000000111101100000000
> 00000000001111111110000000
> 00000000011111111100000000
> 00000000111111111111100000
> 00000001111111111111010000
> 00000011111111111111010000
> 00000101111111111110011100
> 00001111011110110101011100
> 00000111111111111111110000
> 00000011110011100101100000
> 00000001111111111101100000
> 00000001111111110100000000
> 00000000011111110110000000
> 00000000010101010000000000
> 00000000000010110000000000
> 00000000000110111000000000
> 00000000000110110000000000
> 00000000000010100000000000
> 00000000000000000000000000
> 00000000000000000000000000
> 00000000000000000000000000
>
> 00000000000000000000000000
> 00000000000000000000000000
> 00000000000000000000000000
> 00000000000000100000000000
> 00000000000001110000000000
> 00000000000001111000000000
> 00000000000011111000000000
> 00000000000111111100000000
> 00000000001111111100000000
> 00000000011111111111000000
> 00000000011111111111000000
> 00000001111111111111100000
> 00000001111111111111110000
> 00000011111111111111111100
> 00000111111111111111111100
> 00001111111111111111111100
> 00001111111111111111111000
> 00000111111111111111110000
> 00000011111111111111100000
> 00000001111111111111000000
> 00000000111111111110000000
> 00000000011111111100000000
> 00000000001111111100000000
> 00000000000111111000000000
> 00000000000111110000000000
> 00000000000011110000000000
> 00000000000011100000000000
> 00000000000001000000000000
> 00000000000001000000000000
> 00000000000000000000000000
>
>
> Thanks,
>
>
> --
> (B=) <-----my sig
> Brian Schott
> ----------------------------------------------------------------------
> For information about J forums see http://www.jsoftware.com/forums.htm
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