Resumen
To improve the accuracy of non-contact measurements of animal body size and reduce costs, a new monocular camera scanning equipment based on structured light was built with a matched point cloud generation algorithm. Firstly, using the structured light 3D measurement model, the camera intrinsic matrix and extrinsic matrix could be calculated. Secondly, the least square method and the improved segment?facet intersection method were used to implement and optimize the calibration of the light plane. Then, a new algorithm was proposed to extract gray- centers as well as a denoising and matching algorithm, both of which alleviate the astigmatism of light on animal fur and the distortion or fracture of light stripes caused by the irregular shape of an animal?s body. Thirdly, the point cloud was generated via the line?plane intersection method from which animal body sizes could be measured. Finally, an experiment on live animals such as rabbits and animal specimens such as fox and the goat was conducted in order to compare our equipment with a depth camera and a 3D scanner. The result shows that the error of our equipment is approximately 5%, which is much smaller than the error of the other two pieces of equipment. This equipment provides a practicable option for measuring animal body size.