Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Improved classification and segmentation of hyperspectral images using spectral warping
International Journal of Remote Sensing
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
IEEE Transactions on Information Theory
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Ultraviolet Spectra (UVS) analysis is a frequent tool in tasks like diseases diagnosis, drugs detection and hyperspectral remote sensing. A key point in these applications is the UVS comparison function. Although there are several UVS comparisons functions, creating good dissimilarity functions is still a challenge because there are different substances with very similar spectra and the same substance may produce different spectra. In this paper, we introduce a new spectral dissimilarity measure for substances identification, based on the way experts visually match the spectra shapes. We also combine the new measure with the Spectral Correlation Measure. A set of experiments conducted with a database of real substances reveals superior results of the combined dissimilarity, with respect to state-of-the-art measures. We use Receiver Operating Characteristic curve analysis to show that our proposal get the best tradeoff between false positive rates and true positive rates.