martedì 1 luglio 2014

Scanning transmittance NIR imaging system using LEDs matrix and Python.

NIR transmittance imaging is a techniques used in cultural heritage diagnostic. Similarly to reflectography, NIR transmittance imaging used a NIR source and a sensor able to detects these wavelengths. However in NIR transmittance imaging the painting is between the NIR source and the detector.  Normally a Halogen lamp is used but this has several disadvantages:

  • Warms the painting. 
  • Some light is reflected and diffused from the surrounding objects, and so is quite difficult to obtain a pure transmittance image.
  • Not so easy to handle.
Using a little LED matrix can resolve all this problems adding further advantages:

  • LEDs produce narrow light spectra, so generally you don't need a IR-PASS filter in your camera, this means that theoretically you could generally achieve a better MTF.
  • There are available different type of IR LEDs operating in different NIR region (940 nm, 850 nm etc. etc.) so basically you can build cheaply a multispectral imaging system. Or even multispectral polarized imaging system... 
There is only a big problem: how can you analyze a large surface using a little LEDs lamp? I have tried to solve it using a simple algorithm.

NIR transmittance imaging using a little NIR LEDs  matrix  at 940 nm .



Suppose you are in a completely dark room recording a video, the painting appear black in the area where is not lighted, moving the lamp when a different area is lighted the pixel values increase. So when you scan the painting surface with your lamp, keeping your lamp at a fixed distance basically what you need is to substitute the unlighted with the lighted ones. So the algorithm compare the same pixel and keep the highest value. You can compare the same pixel of an acquisition with the next acquisition or you can set a threshold (something like: if pixel>background and pixel < 255: result_pixel=pixel). The first solution is quite simple to achieve using Python, keeping all the snapshot in a folder you can use this script:
from PIL import Image,ImageChops
from os import listdir,sep
def FolderElab():
    foldername=r'/home/giacomo/Documents/Foldername'
    folder=listdir(foldername)
    fused=Image.open(foldername+sep+folder[0])
    for i in folder:
        orig=Image.open(foldername+sep+i)
        fused=ImageChops.lighter(orig,fused)        
    return fused 

I've used an old 0.31MP webcam after removing the ICF and substituting it with a piece of floppydisk (as mentioned earlier you can use it without an IR-PASS filter, however sometimes could be easier install one to operate in lit rooms). This is the first result, merging all the images.

Resulting image made of different images as the previous one.

Python script to collect LEDs matrix data.

Analyzing a LEDs matrix one LED by one reporting data in a spreadsheet and then analyzing it could be very time consuming. A simple python script can speed up a little bit the tests, organizing the data and plotting the result. The resulting image, automatically generated using matplotlib, show the mean and the standard deviation for every LED and resistance in the circuit. You can specify the number of rows and columns depending on your matrix.

Code is hosted on gitHub.