The invention relates to a skin quality detection method based on a big data algorithm. The skin quality detection method comprises the following steps: 1, establishing a human face skin sample library; 2, obtaining a training sample set and a to-be-identified sample; 3, extracting the textural features and the RGB color information of the small color image blocks; 4, training a VGG16 classifier;5, classifying the small color image blocks in the to-be-identified sample set; and 6, obtaining the proportion of the number of the small color image blocks in each category to the total number of the small color image blocks to obtain a skin quality detection result. According to the method, the accuracy of detection of complex and changeable circular skin problems, such as skin color detection,skin age detection, left and right single and double eyelids, eye bags, dark circles, forehead wrinkles, crow's feet, eye wrinkles, nasolabial folds and skin quality detection is improved, the severity of various skin problems can be analyzed, and the reliability of human face skin quality analysis is improved. The method can be applied to automatic vending equipment.