Detection and Classification of the Foreign Matter of Lyophilized Powder Based on Machine Vision
DING Jinru
MENG Zhigang
YANG Yanhe
Abstract：In this paper,digital image processing technology is used to detect and classify the foreign matter of lyophilized powder.In order to more efficiently detect and classify the existing foreign matter in lyophilized powder such as fibers,hair,particles of glass and other visible foreign matter,BP neural network and support vector machine (SVM) algorithms together with principal component analysis (PCA) feature extraction are used to do classification and recognition.Through industrial small sample data simulation,test results show that both methods have good feasibility and practicability.By comparison it is showed that the recognition based on PCA and SVM algorithm is higher than the recognition based on PCA and BP algorithm.
Keywords：inspection of obviously foreign matterprincipal component analysis(PCA)BP neural networksupport vector machine(SVM)
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 29-33,121 )