Research on Pig Weight Prediction Algorithm Based on Machine Vision and Random Forest

In this paper, a pig weight prediction algorithm based on machine vision and random forest is proposed. The external features of pigs are extracted by image processing technology, and the weight prediction is carried out by combining random forest algorithm. Initially, a high-resolution camera captured an image of the pig, and subsequently, an image processing algorithm was employed to extract features such as the pig's geometric characteristics, encompassing body size, length, and height. Then, the extracted features are input into the random forest model for training and testing, in order to establish an accurate weight prediction model. The experimental outcomes demonstrate that the proposed algorithm exhibits high precision and robustness in predicting weight. In comparison to the conventional weight measurement approach, this algorithm not only minimizes labor costs but also enhances the efficiency of data acquisition.