Discrimination method of big data complex features of ancient lacquerware paint film

Abstract

The invention discloses a discrimination method based on big data complex features of ancient lacquer ware paint films, which comprises the following steps: extracting data features from existing authentic samples of ancient lacquer ware paint films, including chemical composition features, microscopic image features, scanning electron microscope X-ray energy spectrum features, Fourier transform infrared spectrometer features, and Raman spectrometer features; according to the extracted data features, a sample library and a pattern recognition classifier for ancient lacquer ware paint films are established, and the existing authentic samples of ancient lacquer ware paint films , respectively carry out label calibration; obtain the data characteristics of the unknown lacquer paint film to be detected and identified, and compare it with the parameters in the sample library to obtain the optimal matching result. If the matching is successful, the category and process of the sample to be tested will be identified. and age prediction results, otherwise the classifier will prompt abnormal information to complete the identification of lacquerware paint film. The invention provides a scientific method for inferring the authenticity of cultural relics, age identification and process identification of the lacquerware paint film.

Description

Technical field [0001] The present invention relates to cultural relics discriminating, chemical composition, and spectral analysis, image pattern identification areas, in particular, refers to a large data composite feature discrimination of an antimicer paint film. Background technique [0002] With the application of modern inspection instruments and big data, pattern identification technology, in the field of cultural relics, the era, process identification and authenticity differential areas, using modern instrument testing methods, and combined with computer large data processing methods to develop hotspots . The artifact identification and discrimination method based on mode identification can obtain scientific and accurate decision-making results, which have many advantages compared to artificial discipline. [0003] From the current research application, the use of X-ray detection, Raman spectroscopy, Fourier infrared spectroscopy, etc., the chemical composition of lacqu...

AI Technical Summary

Problems solved by technology

[0004] 1. The use of instrumental analysis focuses on the analysis of the internal composition of the lacquerware paint film. Generally, individual samples are tested one by one, and there is a lack of inductive storage and systematic analysis of batch testing data;

[0005] 2. Determine the composition content of the instrument detection data, and compare it with the spectral image of the standard substance. Although a relatively accurate judgment can be made within the error tolerance range, there are often many kinds of components in the actual lacquerware paint film. The elements are mixed, and the detected data often cannot reflect its real material composition and content;

[0006] 3. The process discrimination, age and classification of lacquerware paint film are generally based on observation and experience, lack of data support, resulting in unobjective results

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