Multi-classification Face Recognition Method Based on Mixed Kotz-type Distribution
Yuan Shao-fen · Jisuanji gongcheng · 2013
Aiming at the problem of the heavy-tailed characteristics in the actual face image, a face recognition method of multi-classification based on mixed Kotz-type distribution is proposed. Mixed Kotz-type distribution and generalized inverse gamma distribution are often used to represent heavy-tailed characteristics. Based on kernel method and probability statistics, this method adjusts the mixed Kotz-type distribution of the parameters to estimate the facial image in the case of heavy-tailed noise tailing. Varying degrees of heavy-tailed noise are added respectively to the ORL face database, Yale face database, Randface(homemade) face database, and a new heavy-tailed noise with varying degrees of face database is formed. Through the verifying of three face database containing different level heavy-tailed noise, results show that the method can estimate the face image trailing feature containing heavy-tailed noise, and has a higher recognition rate.