Individual identification and behavioural analysis of pigs is a key link in the intelligent management of a piggery, for which the computer vision technology based on application and improvement of deep learning model has become the mainstream. However, the operation of the model has high requirements to hardwares, also the model is of weak interpretability, which make it difficult to adapt to both the mobile terminals and the embedded applications. This study proposes to first use the LDA method to extract the main features of the pig’s face, and then conduct an individual recognition test based on the face image, and reach an average accuracy of 64.9%, This method not only reduces the computational complexity but also is of strong interpretability, so it is suitable for both the mobile terminals and the embedded applications. In some way, this study provides a systematic and stable guidance for livestock and poultry production.