November 30, 2009

Wikipedia’s list of image analysis software

Wikipedia’s article lists image analysis software in the form of a table. The columns are:

  • Product  
  • Developer 
  • Cost (USD) 
  • Open source 
  • Software license  
  • OS 
  • Continuous 
  • Industries, Uses and Applications

I thought that the type of license, open/closed source, OS, etc aren’t very interesting, while some more important, in my view, data should be added. Based on the inspection of the vendors’ sites, I tried to answer the following questions.

What is the price? In the absence of that information, I put $$$$ indicating that the price might be in the thousands.

Is there a free version available for download? Companies with $$$$ usually don’t have that.

Does the site provide examples of how the software has been used for image analysis? Very often, surprisingly little is provided.

Does the site reveal the methods/algorithms behind the software? Commercial vendors say nothing. Open source certainly qualifies for Yes in this category but most of the time the source is all you get. The actual math, algorithms, errors, etc are ignored.

To see the new table follow this link: Image analysis software.

November 27, 2009

No web apps, for now

Filed under: image processing/image analysis software,updates — Peter Saveliev @ 11:15 am

Q. “I was wondering if it is possible to make it as an online service where people could log on to the server and upload their image and obtain the report or csv file.”

A. I have been thinking about a web app for Pixcavator for a while. The idea is certainly very attractive but there are some drawbacks. First, the computations that Pixcavator does are quite CPU and memory intensive. The testing that has been done shows that online computation (short of some kind of supercomputer) wouldn’t be any faster than if it is done on a modern PC. Second, uploading a 1000×1000 bmp file can take as long as the processing itself. Once it becomes common for people to keep their images (and I mean business/research images, not family albums) “in the cloud”, a web application will make more sense. Getting there may take some time but there is no doubt in my mind that this is the future.

November 16, 2009

Tumor demarcation: an image analysis challenge

Filed under: image processing/image analysis software,reviews — Peter Saveliev @ 11:46 pm

These images came from researchers in medical image analysis. They represent “low-intensity multi-spectral image of the tumour in the early stage of development”. Their algorithm has been patented and the results are published in Medical Image Analysis.

Image:High-intensity_fluorescent_image.jpg Image:Low-intensity_fluorescent_image.jpg

The images below came from the same source and show the results of analysis of the first image by means of their algorithm (right) vs. Pixcavator’s (left). The comparison is unfavorable.

Image:Pixcavator_vs_NDCA.jpg

I ran Pixcavator myself with the first image, high intensity. I had to move the maximal contrast slider and in about 5 seconds I had a satisfactory result, below.

The low intensity image is here.

November 11, 2009

Everyone should see these images…

Filed under: computer vision/machine vision/AI,education,mathematics,news — Peter Saveliev @ 3:49 pm
… whether you work in image processing and analysis, computer vison, mathematics, or even arts.
click the image to see more
These amazing images show the 3D Mandelbrot set.

From simplicity comes complexity. And beauty!

November 6, 2009

Particle statistics with calibration: an image analysis example

Filed under: image processing/image analysis software — Peter Saveliev @ 4:50 pm

The task for Pixcavator: “What I need it for the software to analyse the attached image in order to get an area for each particle. I compare the area with a standard 2mm square that is included in the image. I then take the values and create a histogram showing the size distribution of the particles.”

I analyzed the image with these settings: 20, 10, 0, 69, 0, 255. The image is below.

I unmarked the light objects and saved the spreadsheet. Then I did some data processing with Excel. First I located the square, line #3248. Its area is 211, so:

 211 pixels = 2 mm * 2 mm
= 4 sq mm and 1 pixel
= 4 / 211 sq mm
= .019 sq mm.

I used the last number as the calibration factor in the other spreadsheet. It contains the areas in mm. It also contains the histogram of distribution of the area. I think the results make sense.

Image:particles statistics.jpg