This came from an environmental researcher: “I need to determine the circumference of a coral lesion with a metric stick in the same picture.” The goal is to “determine how well corals are able to recover from damage or stress”.

This is what I was able to do with Pixcavator in about 10 minutes.

First, I cropped the image to speed up processing time. Then I ran the analysis. To capture the lesion I had to move the first slider almost all way to the right. The green contour then appears to capture the lesion well enough - the first screenshot. (The same result can be obtained using the other sliders.) Then in the table on the right you can see the size (area) of the spot: 19516 pixels. If you want to find the diameter, you can treat the spot as a circle with area 19516. Then the diameter is 2*sqrt(area/Pi) = 158.

Now, this result is in pixels. Pixcavator does not have at this time an automatic calibration feature but it can be done nonetheless. Out of many ways to do it - turn pixels into centimeters - I chose just one. In the second screenshot you can see that I captured two lines on the stick. Their second coordinates are 225 and 258. Then we have 5mm = 258 - 225 = 33 pixels. So the diameter is 158/33*5 = 79 mm which is reasonably close to what you see. If the setup is always the same, the calibration part will have to be done only once.

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I gave a talk at the WORDCOMP conference in Las Vegas, specifically IPCV’09, International Conference on Image Processing, Computer Vision, and Pattern Recognition. Here is the slides with comments. It also makes sense to look at the paper the talk came from.

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I spent two weeks attending lectures (three every weekday!). It was the IMA New Directions Short Course Applied Algebraic Topology at the Institute for Mathematics and Its Applications at the University of Minnesota. The main focus was on how the methods of algebraic topology can contribute to data analysis. I am quite certain that there is a big future here (in fact, I’ll add article Topological data analysis to the wiki soon). Sensor networks, robotics, and dynamics were also discussed.

The main link with all the lectures is this: http://www.ima.umn.edu/2008-2009/ND6.15-26.09/. Another good site is due to Gunnar Carlson, one of the organizers. It is called TMSCSCS: Topological Methods in Scientific Computing, Statistics and Computer Science. A lot of interesting preprints here as well as jPlex, the software that actually does the computations that we discussed. There is also a Wikipedia article. A Google group was formed by the participants.

I am working on a paper that will summarize my views on this stuff, as it fits both data analysis and computer vision…

Next for me is the WORDCOMP conference in Las Vegas, July12-17. I’ll be giving a talk at IPCV’09, International Conference on Image Processing, Computer Vision, and Pattern Recognition. It will be based mainly on the last paper of mine.

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