Offset printing ink color matching method based on least squares support vector machine

Abstract

The invention relates to the field of a printing technology and particularly relates to an offset printing ink color matching method based on a least square support vector machine. The offset printing ink color matching method comprises the following steps of: sampling each foundation ink according to different concentration gradients, mixing foundation inks with m concentration ratios selected within a (1-100)% range of the concentration gradients with a reducer, and then measuring an XYZ value corresponding to each standard color sample obtained by sampling; obtaining an XYZ value of a target sample to be matched, and selecting N inks for color matching, so as to obtain m*N XYZ values and corresponding concentration ratio training sample data; training an LS-SVM (Least Square-Support Vector Machine) function model, and establishing relation of the XYZ values and an ink matching formula, so as to convert the XYZ values into the ink concentration ratios; and inputting the XYZ value of the target sample to be matched into the trained LS-SVM function model, so as to obtain the corresponding ink formula through calculation. With the adoption of the offset printing ink color matching method provided by the invention, the precision requirement on a foundation ink database is small, the color matching is simple and convenient and reliable, and the efficiency is high.

Description

technical field [0001] The invention relates to the technical field of printing, in particular to an offset printing ink color matching method based on a least squares support vector machine. Background technique [0002] In recent years, with the rapid development of computer technology, computer color matching technology has been gradually applied to the field of printing and packaging. At present, the common ink color matching algorithms include the following: [0003] 1. Database search method: a method based on interpolation theory, which has high requirements for the amount of sample data. It is similar to an enumeration method. The more sample data, the more accurate the calculation results are, and the practical application is more difficult; [0004] 2. Spectral matching method: It is an ideal color matching method, but it has high requirements for the materials involved in color matching, and the ink and substrate materials involved in color matching are required t...

AI Technical Summary

Problems solved by technology

[0005] 3. Three-stimulus value matching method: it is necessary to establish an accurate basic ink database, and the cost of building a database is relatively high;

[0006] 4. BP neural network method: A large number of samples are required for learning, otherwise the accuracy of the model is low. At the same time, the training process is very sensitive to learning samples. Once an error sample occurs, the model will become very inaccurate

However, the current tri-stimulus value color matching algorithms all need to establish an accurate basic ink database, that is, carry out gradient concentration proofing for each basic ink and input it into the computer to calculate the unit concentration KS value that characterizes a certain ink characteristic, and use it as The basic data establishes the basic ink database. The accuracy of the basic ink database has a great influence on the computer color matching effect. Therefore, for printing companies, it is necessary to ensure the stability of the experimental conditions and the accuracy of the experimental operation when building the database.

Therefore, using this method to build a database in the early stage requires a lot of manpower and material resources, and the cost of building a database is very high.

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