Baseline spliting of traditional Chinese medicine fingerprint based on the second-generation wavelet transform

In order to overcome the disadvantages of the conventional data pre-processing technology for the fingerprint signals of traditional Chinese medicine, such as complexity and low speed of the algorithm, the features of fingerprint signals are analyzed, on the basis of which a new method is then proposed. In this method, the second-generation wavelet transform technology, the local reconstruction technology and the Daubechies wavelet-lifting method are adopted to split the baseline of traditional Chinese medicine fingerprint. The experimental results of Tianjihuang fingerprint according with the AIA standard show that the proposed method can effectively split the baseline from the signal peak with great precision and is easy to be implemented by software.