Related works

Below is a paper Serge recommended, while it happens to be a paper that demonstrates a possible method that I may be familiar with.
http://physics.fme.vutbr.cz/libs/images/stories/publikace/2001/Lecture%20Notes%20in%20Computer%20Sciences_2001.pdf
(Data below is collected from this paper)


1.WHAT DID THEY GET

LIBS (Laser Induced Breakdown Spectroscopy) spectra is collected for samples of several materials. The picture below shows spectra of (a) aluminium, (b) copper, (c) lead, (d) zinc, (e)mild steel, (f) stainless steel and (g) vitrification glass

Each spectrum collected using a LIBS instrument is a “finger-print“ of the material being analysed and the conditions under which it was collected. 

So we can identify a kind of material by analysing its spectrum.

2.HOW DID THEY ANALYSE IT

Here they used the Mahalanobis Distance method to evaluate the distinction of sample material and the criteria, and then give a discrimination of the material.

The M.Dist applies to all pixels in the spectrum, not just to

one or two pixels of a peak, and therefore can be considered to be a multi-dimensional standard deviation that is applied to the whole spectrum.

I think this may be a possibe solution to our question.

3.WHY IS THIS PROJECT DIFFERENT

In contrast, this is "an example of a project doing material recognition from regular images"  http://people.csail.mit.edu/celiu/CVPR2010/FMD/index.html

It is more relied on a large dataset, but don't need a device. But mine may need to programme on a scanner to get the properties of the material and identify them.