Acne is a chronic inflammation of the skin veins of Propionibacterium, which endangers human health. Although there are acne identification methods on the market, their instruments are large and expensive, and there is currently no civilian-level acne identification system in use. This paper proposes a facial acne recognition scheme based on multispectral imaging technology, that is, using multispectral camera equipment to collect multispectral image information for normal and acne skin of different severity on the face, multispectral image analysis of the collected information by image processing method, and obtain spectral information through spectral inversion algorithm. The reflectance lines of normal and acne of different severities are then compared with the trend of the lines detected by the high-precision spectrometer under the same experimental conditions. Finally, a three-degree and four-level classification model of facial acne in the support vector machine was established with an accuracy rate of 90%, which verified the feasibility of non-invasive identification and classification of facial acne based on multispectral imaging technology.