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	<title>Computer Vision For Dummies</title>
	<link>http://inperc.com/blog2</link>
	<description>Computer vision and image analysis for newcomers</description>
	<lastBuildDate>Fri, 05 Mar 2010 15:59:51 +0000</lastBuildDate>
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	<language>en</language>
	
	<item>
		<title>ImageJ vs Pixcavator: update</title>
		<description>Two years ago I had a post here (follow-up) where I dared to compare these two programs. The reaction was unfavorable. The ImageJ ticket quoted below seems to indicate that there has been a slight shift.
Wayne [Rasband] had an idea for a command called "Analyze Image" that combines filtering, background correction, segmentation, ...</description>
		<link>http://inperc.com/blog2/2010/03/05/imagej-vs-pixcavator-update/</link>
			</item>
	<item>
		<title>Update on CHomP, homology software</title>
		<description>Prof. Marian Mrozek  was kind enough to inform me about the coming update of CHomP in his email that I quote below:
The power of the software comes from much newer algorithms. Some of them are described in the papers:

	M. Mrozek, P. Pilarczyk, N. Zelazna, Homology algorithm based on acyclic subspace, Computers and Mathematics ...</description>
		<link>http://inperc.com/blog2/2010/03/03/update-on-chomp-homology-software/</link>
			</item>
	<item>
		<title>Analysis of RGB channels in color images</title>
		<description>


 

RGB stands for Red, Green, and Blue. These are the "channels" in a color image. Each pixel has 3 numbers between 0 and 255 assigned to it.

	(255,0,0) red,
	(0,255,0) blue,
	(0,0,255) green,
	(255,255,0) yellow,
	(255,0,255) magenta,
	(0,255,255) cyan,
	(g,g,g) gray, for any g,
	(0,0,0) black,
	(255,255,255) white


Every color image has three color channels - red, green and blue ...</description>
		<link>http://inperc.com/blog2/2010/02/26/analysis-of-rgb-channels-in-color-images/</link>
			</item>
	<item>
		<title>Plans for the site</title>
		<description>Most of the recent content has come from two main sources. First, I have been adding, as before, examples of image analysis from the users of Pixcavator. The second is the course I've been teaching since last fall: Introductory algebraic topology. I plan to add more content from the courses ...</description>
		<link>http://inperc.com/blog2/2010/02/22/plans-for-the-site/</link>
			</item>
	<item>
		<title>Measuring seedling area: an image analysis example</title>
		<description>
Q: We need to "measure all the seedlings area (by dividing by the number of them I can get indication to their area and structure, and other parameters I can get)... The area covered is 80*80cm."

The screenshot shows the results of my experiment. Here the red contours surround the darker ...</description>
		<link>http://inperc.com/blog2/2010/02/17/measuring-seedling-area-an-image-analysis-example/</link>
			</item>
	<item>
		<title>Hose measurements: an image analyis example</title>
		<description>


Q: We "need to verify the internal diameter, external diameter and the wall thickness between the ID, OD and the reinforcement yarn. One issue we have is that the wall is not always concentric. We have a minimum wall thickness specification so we would like to measure the wall thickness ...</description>
		<link>http://inperc.com/blog2/2010/02/10/hose-measurements-an-image-analyis-example/</link>
			</item>
	<item>
		<title>Pixcavator 5.0 released</title>
		<description>These are the new features in version 5.0.

	Your choice of settings in the Output tab (the position of the sliders) is preserved when you load a new image to analyze.
	Your choice of color channels in the Analysis tab is preserved when you load a new image to analyze. With these ...</description>
		<link>http://inperc.com/blog2/2010/01/31/pixcavator-5-0-released/</link>
			</item>
	<item>
		<title>Topological data analysis</title>
		<description>

Below is the abstract of a paper I am working on.

Suppose we have conducted 1000 experiments with a set of 100 various measurements in each. Then each experiment is a string of 100 numbers or simply a vector of dimension 100. The result is a collection of disconnected 1000 points ...</description>
		<link>http://inperc.com/blog2/2010/01/25/topological-data-analysis/</link>
			</item>
	<item>
		<title>Cluster size effects in molecular beam scattering: research that uses Pixcavator</title>
		<description>

A new research paper that uses Pixcavator:

Adsorption Dynamics of CO on Silica Supported Gold Clusters: Cluster Size Effects in Molecular Beam Scattering Experiments by E. Kadossov, U. Burghaus (Department of Chemistry, Biochemistry, and Molecular Biology, North Dakota State University), link, published in Catalysis Letters.

From the paper:

"We report on particle size ...</description>
		<link>http://inperc.com/blog2/2010/01/13/cluster-size-effects-in-molecular-beam-scattering-research-that-uses-pixcavator/</link>
			</item>
	<item>
		<title>Pixcavator Single Image Edition</title>
		<description>This edition is a version of Pixcavator that comes with a preloaded image. Which means that it's not really a single program but many - one for each image.

It is a single file "exe" program that does not require any installation. As such it can be used as an alternative ...</description>
		<link>http://inperc.com/blog2/2010/01/11/pixcavator-single-image-edition/</link>
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