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Implementing Principal Component Analysis Image Segmentation

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21 Jun 2024CPOL3 min read 4.2K   92   8  
How to implement principal component analysis clustering algorithm to perform image segmentation.
We can bisect an image into two areas of similar colour by taking the principal component of variation and then using Otsu thresholding to select the point at which to cut. Further bisections of clusters with the highest error are then bisected until a segmentation of the desired number of segments is produced. This algorithm is invented by myself and so is not well tested.

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


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I started programming when we were taught Basic on the Commodore Pet at school, and was immediately hooked. But my parents were not generous with money, and it was a while before I saved up enough money to buy a second-hand ZX81. Then a friend gave me "Machine Code on your ZX81" by Toni Baker (not "Tony", a lady), and that book changed my life, because it enabled me to master something that most adults couldn't do. And I realised the power of good textbooks and self study. I have written two books on programming in consequence.

Then I want to Oxford to study English Literature, and programming came to an end, except for a brief course on Snobol, and statistical analysis of grammar words (words like "and" and "he"). But the expected job with the Civil Service did not materialise, I needed to earn a living somehow, and so it was to games programming that I turned. But I was never entirely happy as a game programmer. Whilst I enjoy programming games, I'm not so fond of playing them, except for Dungeons and Dragons style games. And for a games programmer, that's a big handicap.

I've got other interests aside from programming, and after I had collected a big pile of cash from games programming, I decided to spend it on doing a second degree, at Leeds University, in biology. That then led naturally to a PhD in computational biochemistry, working on the protein folding problem, and that turned me into a really good programmer.

However there's only one faculty position for every 10 PhDs, and I was one of the unlucky nine, and so I found a job doing graphics programming. Which I kept until unfortunately ill health forced me to give up work. And I am now a full time hobby programmer.

And my main project is Baby X and its attendant subsystems.


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