Abstract: A feature extraction and classification method based on support vector data description is provided, which includes: calculating, for each sample, Euclidean distances from the sample to spherical centers of multiple hypersphere models corresponding to different data categories, where the multiple hypersphere models are acquired in advance by training using a support vector data description algorithm; substituting, for each sample, the Euclidean distances and radiuses of the hypersphere models respectively corresponding to the Euclidean distances into a new feature relation equation, to acquire a new feature sample corresponding to the sample, where the new feature samples constitute a new feature sample set; and performing classification on the new feature sample set using a preset classification algorithm, to acquire a classification result. A feature extraction and classification system based on support vector data description having the above advantages is further provided.