一种纳米颗粒上转换发光防伪编码方法

A novel anti-counterfeiting encoding method based on the nanoparticle upconversion luminescence is proposed. This method combines the image processing algorithms based on MATLAB, support vector machine (SVM) classification and radial basis function neural network classification. With the analysis of the upconversion luminescence spectral characteristics of the green and red lights emitted from the nano-materials which are pumped hy the 980 nm laser, and the spatial distribution characteristics of these nano-materials on the anti-counterfeiting substrate, the anti- counterfeiting method with a high-security and an automatic capability of database building and pattern recognizing is realized. The experiment confirms that it is difficult to replicate the prepared anti-counterfeiting markings whose characteristic patterns have a high stability, and the identification accuracy is up to 95.4 % .