[Image-SIG] Image-SIG Digest, Vol 59, Issue 7

[Abhishek Pathak]

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Today's Topics:

   1. Area selection marquee (C Krause)
From: C Krause <ckrause at meraka.org.za>
To: image-sig at python.org
Date: Mon, 10 Mar 2008 11:07:02 +0200
Subject: [Image-SIG] Area selection marquee

 I am programming a colouring book and need to identify all the distinct 
bound areas on an image so that i can cycle through them (and if 
possible convert them to separe image objects. (see the magic wand 
selector in any paint application) I also need a flodd fill routine - 
please help me as I am a newbie with Python - Thaks Chris Krause

Hi,
I can't help you with python code, but I can definitely tell you the solution in general terms. My reply is: 
1. For extracting the distinct areas in the image, use either (a)segmentation approach, or (b) edge detection approach (c) Morphological boundary extraction.
I will detail on (b) & (c)
(b) Use either of the following convolution masks :
Sobel, Prewitt, Robert-Cross (only 2x2 exists), or make your own
Sobel is by far the best, as per what I have seen. You may choose a 3x3 mask
for sharper edge-detection, or a 5x5 or 7x7 mask for thicker detection with heavier response.
A 9x9 mask also exists, which you may try i9f Sobel doesn't work. It is Laplacian of Gaussian.
(c) 
Step1 : represent the object/image using any set representation, (see Set Theory in case of doubts),
Step 2:  take the dilation of the image, 
Step 3 : subtract (***Set Subtraction***), from it the image, and you got the boundary.
This method of morphology is for binary image only, and for grayscale/colour images, it is far more complex than this one.

This is the theory of the technical stuff. I haven't done much programming in python, so can't give code for that, except for representation and basic operation on sets.


Bye.

       
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