Research on Kinect Segmentation Algorithm Based on Pig Point Cloud

Since arrival of new era of socialism with Chinese characteristics, living standards and quality of life of people have gradually improved. Farmers hope to obtain physical signs of livestock without causing stress reactions, and this demand is gradually increasing. Moreover, animal protection personnel hope to gradually increase requirement for measuring physical characteristics of animals without disturbing them. Therefore, method proposed in this article enables breeders and animal protection personnel to achieve hope of non-contact measurement to obtain animal signs. Contactless measurement has always been one of main research directions in machine vision, using point cloud segmentation method to filter out background point cloud ground and railing of pigs under complex conditions. Point cloud segmentation is a prerequisite for all basic applications, not only for point cloud reconstruction but also for segmentation and classification applications. In point cloud segmentation, a random sampling consensus algorithm (RANSAC) combined with conditional Euclidean clustering segmentation algorithm is proposed. Using single choice point cloud segmentation to divide entire point cloud into two parts, effectively obtaining target point cloud information.