You may be able to modify the code discussed in this thread for automatic point-to-point measurements: https://www.researchgate.net/post/How_to_measure_point-to-point_distances_in_ImageJ. You may need add some type of Segmentation (http://imagej.net/Segmentation) to help with finding the edges of your discs.

I find that it is the selection process (usually some type of ROI) that causes me to need to go through each image manually - there is usually some type of qualitative parameter that the computer has a hard time picking out on its own. If there are a series of steps that you find -- menu options and/or plugins/macros -- that don't require the qualitative assessment, then you can create a macro using the Macro Recorder and then process all of your images in a Batch Process.

With tree cores and discs, I have measured a lot of tree ring widths. I use the following line segmentation code installed as either a macro or plugin:

macro "ListSelectionCoordinates" {

if (selectionType==-1)

exit("Selection required");

getSelectionCoordinates(x, y);

getPixelSize(unit, pixelWidth, pixelHeight);

run("Clear Results");

count = 0;

n = x.length;

for (i=0; i

I did a bit of this in the 90's looking at the best approach to minimise shrinkage in drying SilviScan samples.  One of the issues was getting a good image without shadowing around the edges which adds to the variability in assessing the edge of the strip.

I used a language that is not available now but you could do the same thing using R.  Essentially the approach was to binarise the image and then measure the width variation down the strip. You can see something similar in our paper.

Downes G.M., Touza M., Wentzel-Vietheer M., Harwood C.E. (2014) NIR detection of non-recoverable collapse in sawn boards of Eucalyptus globulus Eur. J. For. Prod 72(5) 563-570 DOI: 10.1007/s00107-014-0813-9.

Have a look also at 

Hamilton, MG and Potts, BM and Harwood, CE and Apiolaza, LA and Gore, PL (2004) Comparison of non-destructive assessment techniques for shrinkage and collapse in Eucalyptus nitens. In: Eucalyptus in a Changing World. Proc. of IUFRO Conf., Aveiro 11-15 October 2004, 11-15 October, Aveiro, Portugal.

Hi George,

I would strongly recommend you take a look at MIPAR at http://MIPAR.us. I am the primary developer of this new software, but I can tell you also as an end user that is has been extremely versatile at building non-destructive, flexible recipes (like macros but much better!) which have solve many challenging image analysis problems. The measures from these segmentations are fully automatable as well. I'd be delighted to take a look at any example images you could provide and build a recipe for your needs!

Cheers,

John

Thanks for the answers guys, I'll have a  look and perhaps contact you individually for further discussions!