Minimum description length approach to detecting chemicals via their Raman spectra

Ryan D. Palkki; Aaron D. Lanterman

doi:10.1117/1.3609805

1 August 2011 Minimum description length approach to detecting chemicals via their Raman spectra

Ryan D. Palkki, Aaron D. Lanterman

Author Affiliations +

Optical Engineering, Vol. 50, Issue 8, 083601 (August 2011). https://doi.org/10.1117/1.3609805

Abstract

Raman spectroscopy has provided a powerful means of chemical identification in a variety of fields, partly because of its noncontact nature and the speed at which measurements can be taken. Given a library of known Raman spectra, a common detection approach is to first estimate the relative amount of each chemical present, and then compare the estimated mixing coefficients to a threshold. We present a more rigorous detection scheme by formulating the problem as one of multiple hypothesis detection and using the maximum a posteriori decision rule to minimize the probability of classification error. The probability that a specific target chemical is present is estimated by summing the estimated probabilities of all the hypotheses containing it. Alternatively, since we do not typically have reasonable priors for the hypotheses, it may be preferable to interpret the result as an abstract score corresponding to the minimum description length approach. The resulting detection performance of this approach is compared to that of several other classification algorithms.

©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Ryan D. Palkki and Aaron D. Lanterman "Minimum description length approach to detecting chemicals via their Raman spectra," Optical Engineering 50(8), 083601 (1 August 2011). https://doi.org/10.1117/1.3609805

Published: 1 August 2011

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available