An application of wavelet moments to the similarity analysis of three-dimensional fingerprint spectra obtained by high-performance liquid chromatography coupled with diode array detector

التفاصيل البيبلوغرافية
العنوان: An application of wavelet moments to the similarity analysis of three-dimensional fingerprint spectra obtained by high-performance liquid chromatography coupled with diode array detector
المؤلفون: Yue Li Tian, Hong Lin Zhai, Pei Zhen Li, Bao Qiong Li, Xiaoyun Zhang
المصدر: Food Chemistry. 145:625-631
بيانات النشر: Elsevier BV, 2014.
سنة النشر: 2014
مصطلحات موضوعية: Principal Component Analysis, business.industry, Computer science, Fingerprint (computing), Analytical chemistry, Image processing, Pattern recognition, General Medicine, Grayscale, Analytical Chemistry, Wavelet, Similarity (network science), Chromatography detector, Principal component analysis, Digital image processing, Cluster Analysis, Artificial intelligence, Medicine, Chinese Traditional, business, Algorithms, Chromatography, High Pressure Liquid, Drugs, Chinese Herbal, Food Science
الوصف: More and more the three-dimensional (3D) fingerprint spectra, which can be obtained by high performance liquid chromatography coupled with diode array detector (HPLC-DAD), are applied to the analysis of drugs and foods. A novel approach to the similarity analysis of traditional Chinese medicines (TCMs) was proposed based on the digital image processing using 3D HPLC-DAD fingerprint spectra. As the one of shape features of digital grayscale image, wavelet moments were employed to extract the shape features from the grayscale images of 3D fingerprint spectra of different Coptis chinensis samples, and used to the similarity analysis of these samples. Compared with the results obtained by traditional features including principal components and spectrum data under single-wavelength, our results represented the more reliable assessment. This work indicates that the better features of fingerprint spectra are more important than similarity evaluation methods. Wavelet moments, which possess multi-resolution specialty and the invariance property in image processing, are more effective than traditional spectral features for the description of the systemic characterisation of mixture sample.
تدمد: 0308-8146
DOI: 10.1016/j.foodchem.2013.08.112
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3fb81afad5d8be1cd1d9b47c4cbfd88
https://doi.org/10.1016/j.foodchem.2013.08.112
Rights: CLOSED
رقم الانضمام: edsair.doi.dedup.....c3fb81afad5d8be1cd1d9b47c4cbfd88
قاعدة البيانات: OpenAIRE
الوصف
تدمد:03088146
DOI:10.1016/j.foodchem.2013.08.112