ScanCol24-example:
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This is an example of stained zooplankton scanned at low (600dpi) resolution
with an usual flatbed scanner and saved in the lossy Jpeg format, and without
other calibration than checking the size of the pixel from the scanner
resolution. This approach seems suboptimal (low resolution, no calibration,
lossy compression of data), but it is indeed very easy to use and still
effective to deal with a lot of samples in a short period of time when the
resolution in term of taxa you want to get is low (less than 10 "big" groups).

You can use any kind of flatbed scanner in reflective ("usual" mode) and with
its own driver to digitize your images. This is far more easy than the
transparent mode of the Epson 4870/4990 and the calibration required to obtain
a correct analysis of the huge 16bit graylevels scans with the 'Scanner Gray16'
plugin, or using the Zooscan with ZooProcess. In all cases, the plankton is
simply placed in square Petri dishes on top of the scanner window. We have
found that the cover of traditional microplates are even better containers, and
they are in optically clear polystyren.

These data comes from a cruise in the Bay of Biscay, and they are provided by
Dr Xabier Irigoien from AZTI. Eggs are counter separately and already eliminated
from the preserved sample that is, otherwise, intact. There are just two images
corresponding to two samples (the simplest design, but Zoo/PhytoImage can also
cope with several fractions per sample, several replicates per fraction and
several images per replicates, which is the most complex design, see the other
example datasets for different digitizing strategies).

To run this example:
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- Download and unzip "ScanCol24-example.zip" in your 'ZooPhytoImage Examples'
  directory, or anywhere you like to place it.
  
- Start Zoo/PhytoImage and import the data (second button, select 'Jpeg image
  files' as file type at the bottom of the dialog box and then, select both
  images. Since the images are already in a correct format, nothing is changed.
  The function then checks if the corresponding metadata are there and are
  correct (corresponding .zim files). If not, you are prompted to create them.
  Since the .zim files are also provided and should be correct, the function
  exits almost immediately. Look at the .zim files to get an idea of the kind of
  metadata you need to provide to Zoo/PhytoImage.
  
- Now, you can analyze your image (third button, switch to ImageJ). In ImageJ,
  select (Plugins -> ZooPhytoImage -> Scanner Color). Select one of the .zim
  files you just created and watch the analysis live on screen. You
  can examine the mask and other temporary files in the _work subdirectory.
  
- Once the analysis is done, you can close ImageJ and switch back to the
  Zoo/PhytoImage assistant. Click on the fourth button to finalize the two .zid
  files corresponding to this analysis. You should end up with two .zid files
  (Zoo/PhytoImage Data) plus all the original files moved to the _raw subdirectory.
  
What next...:
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The .zid files are key files in Zoo/PhytoImage. They contain everything you need
for manual and automatic identification of the particles and for the calculation
of summary statistics (abundances, biomasses, size spectra, etc.). At this point,
you can archive (on DVD, external hard disks, etc.) the original data that are
now in the _raw subdirectory to free space on your machine, and safely work with
the .zid files only.

With only two samples, you cannot do much more, but you are supposed to collect
more data, then to train a classifier, check its performances and finally use it
to identify particles in your samples. For examples with more data, switch to the
files whose name ends with 'train&data'.