On 10/22/2013 3:32 PM, Joseph Jacobs wrote:
The best book I have come across for image processing/vision + machine
learning is one by Simon Prince. You can download the book from his
website (http://computervisionmodels.com/). Chapter 13 gives a good
intro to feature extraction.
OK, great -- just what I need! --jv
Joe
On 22 Oct 2013, at 22:27, jim vickroy wrote:
On 10/22/2013 2:47 PM, Joseph Jacobs wrote:
Hey Jim,
From my (non-expert) perspective, performing classification
pixel-wise would not be ideal (please correct me if I am wrong). I
think the better way would be to perform some sort of feature
extraction on the image (eg. SIFT, SURF, HOG, LBP and many, many
more...checkout scikit-image or google it) and to do classification
using that. Which feature extraction method would be ideal for you
and how you apply it would depend on the application.
Thanks for the suggestion; I'll look into that! I'm a novice, but I
agree pixel-by-pixel classification would not seem to scale well. --jv
Not sure how helpful that was.
Joe
On 22 Oct 2013, at 21:10, jim vickroy wrote:
Hi,
Apologies if this is an inappropriate question for this forum.
I have a collection of (1024x1024) mono-chromatic images in which
each pixel is to be labeled as 1 of several categories (e.g., 10).
Furthermore, each mono-chromatic image was captured through several
filters (e.g., 5).
My understanding of the sci-kit documentation is that I would train
a classifier on a pixel-by-pixel basis and then apply it, to new
images, on a pixel-by-pixel basis. Is that correct?
Thanks for your time.
-- jv
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