The application of digital image recognition to the analysis of two-dimensional fingerprints

High-performance liquid chromatography (HPLC) fingerprint has been commonly used in the quality control and assessment of herbal medicines, and two-dimensional (2D) fingerprint obtained by means of HPLC-diode array detector (HPLC/DAD) can provide higher reliability. In this paper, an approach to the analysis of the 2D HPLC/DAD fingerprints, which was based on digital image recognition techniques, was developed for the first time. First, wavelet transform was employed to eliminate noise signal in the 2D fingerprint, and then the 2D fingerprint was converted into grayscale image. Second, several features of the image were calculated, and hierarchical clustering. This approach was applied to the qualitative analysis of the different samples of coptis chinensis, and the clustering result of samples was all highly consistent with the real situation. Based on the densities in grayscale image, three components in standard samples were quantitative analyzed, and the obtained correlation coefficients between concentration and grayscale density were more than 0.999. Our study indicated that the analysis of the 2D HPLC/DAD fingerprint was successful based on the idea and techniques of digital image recognition techniques, and this proposed approach provided a new pathway for the analysis of two-dimensional spectrums.