Statistical bayesian algorithm for processing thermographic images of the cow udder for diagnosing mastitis

Abstract

The article presents results of our experiments carried out to study the invariance of the digital description of the imageThere in the paper is formulated a mathematical problem of multi-hypothetical detection of subclinical and clinical mastitis in dairy cows by the maximum values of udder temperature measured by digital processing of the udder thermal images. The optimal temperature threshold values corresponding to the Bayesian criterion of the minimum average risk in the above multi-hypothesis detection problem are determined by numerical modelling.