PCA/K-L transformation facial recognition method for vending systems.

ABSTRACT: Facial recognition, as an efficient and convenient biometric technology, can be applied to automatic vending systems to achieve functions such as fast checkout and personalized recommendations. To improve the accuracy and processing speed of facial recognition technology, this study designs a facial recognition model for an automatic vending system with an improved principal component analysis method and the Holtling transform. This method reduces the dimensionality of facial features by introducing sample partitioning and histograms into principal component analysis to process facial data. On this basis, the Holtling transform is applied to process the reduced dimensional feature image to obtain the projection value of the face image, making the image easier to recognize. On the renderMe-

SUBMITTER: Lin L 

PROVIDER: S-EPMC12694864 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature