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mattjakob

Kernel (convolution matrix)

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Hello,

I am trying to do some edge detection using a kernel. I need to do this using standard SOPs/VOPs.

http://setosa.io/ev/image-kernels/

outline.png

 

I saw a tutorial from Entagma (https://vimeo.com/169437381) that basically does the operation by hand splitting out the vectors and multiplying them but it's quite tedious and you dont really know what vectors you're multiplying (QUESTION: is there an order in which pcfind returns the array of points eg. clockwise closest to furthest ?)

Is there a better way (using actual matrices / knowing exactly which points) ?

thanks!

 

 

 

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Hey Matt,

PCFind orders the points it returns by distance. As in that example we're searching through a grid with identical distances, I guess in the end it comes down to numerical errors (aka randomness) in which order the points will be returned. There are several ways to write a "proper" kernel, my approach would be VEX in a pointwrangle. However there is this quite stupid hack which allows you to abuse volume convolve in order to do kernel operations on a 2D plane...

Cheers ;)

Mo

Quick_Dirty_kernel_Hack.hipnc

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