The Design And Implementation Of Recognition Method For Liquid Drop Fingerprint Based On Embedded System

Drop analysis technology is an advanced one that can be used to recognize and detect different kinds of liquids. The liquid drop fingerprint which is obtained through drop analysis technology and related instruments reflects several properties of liquid, and it is unique under certain testing conditions. The main purpose in the paper is the research of signal preprocessing, feature extraction, pattern recognition and interaction interface for liquid drop recognition system based on embedded platform.The signal preprocessing methods of liquid drop recognition system are subsection, abnormal drop analyzing, filter design and applications, and normalization. In order to eliminate the influence of abnormal drops for liquid drop fingerprints, abnormal drop analyzing method is designed by feature analyzing of abnormal drops to eliminate the abnormal drops which are obviously different from normal drops. In order to improve the efficiency of filtering, Butterworth zero-phase digital filter is improved according to the Design and application principle of digital filter to realize the convenient modification of filter parameter and the high efficiency of filtering.Feature extraction method of waveform analysis is improved in two aspects: the fitted waveform analysis method based on polynomial fitting, and the dimension reduction method of eigenvalue based on principal component analysis. The fitted waveform analysis method reduces the influence from noise to eigenvalue, though smoothing the curve of liquid drop fingerprint by polynomial fitting. Dimension reduction method improves the efficiency of pattern recognition, by extracting the principal components of eigenvalue based on principal component analysis.For pattern recognition methods, BP neural network recognition method is improved based on clustering analysis, and this improved method is able to reduce the training time and increase the recognition accuracy rate, though classifying liquid samples according to the similarity of eigenvalues and narrowing the recognition range for samples under study. Naive Bayesian recognition method is used in this paper for the recognition of liquid drop fingerprint to achieve relatively high recognition accuracy.Interaction interface for liquid drop recognition system based on embedded platform is designed according to the usability principles. The main functions of this interaction interface are liquid supply control, data acquisition, curve drawing, signal processing and so on.