A new approach for IR spectra matching using normalized local change

Abstract

Spectra matching is widely used in various applications including the search for a spectrum of an unknown compound in an existing spectral database and quality control by means of comparing the spectra of products with standards. In this article, we present a new approach for calculating the similarities of Fourier-transform infrared (FTIR) spectra of organic compounds. Our method, named normalized local change (NLC) approach, incrementally calculates the spectral similarity based on the local spectral shapes. This allows for reducing the bias on the uneven weighing of large and/or broader peaks. In addition, the NLC approach is tolerant to the common issues in spectra matching including baseline offset, baseline sloping, and deviations in wavenumber axis alignment, suggesting its robustness and practical applicability. Performance evaluation confirmed that our NLC approach outperforms commonly used approaches for identifying FTIR spectra of an identical compound in a given dataset.