Peak-searching second derivatives

An automatic peak search is actually the simplest (one-dimensional) case in the more general two- or three-dimensional image recognition problem. Image recognition is easily done by a human eye and a brain but is hard to formalize when random errors are present and, therefore, difficult to automate. Many different approaches and methods have been developed two of them are most often used in peak recognition and will be discussed here. These are the second derivative method and the profile scaling technique. 

Figure 4.8. Automatic peak search conducted using a second derivative method (top) and manually corrected reduced pattern (bottom). The upward arrow placed on the digitized pattern shows a false peak (which was eliminated manually) and the downward arrows show the missed peaks (which were added manually).

Second-derivative i.r. spectroscopy has enabled the separation of sharp peaks from broad structureless continua. Spectra of trace CO2 are used as illustrations. A useful bibliography of published data for i.r. spectroscopy has been provided by Oliver and Marsden. The problem of searching an i.r. reference library using a computer has also been considered. ... 

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