Machine vision-based method for estimating inner wall depth of facility-based crab aquaculture cage

A machine vision-based method for estimating an inner wall depth of a facility-based crab aquaculture cage, comprising:

• acquiring a top-view image of the crab aquaculture cage containing crabs and transparent water body;
• inputting the top-view image into a monocular depth estimation model, and outputting a depth estimation value of each pixel in the top-view image;
• inputting the top-view image into a deep learning based object detection algorithm to determine pixels of a water surface that contact with a front plane, a back plane, a left plane and a right plane of the crab aquaculture cage and excluding other pixels of the transparent water body than the pixels of the water surface that contact with the front plane, the back plane, the left plane and the right plane;
• converting pixel coordinates of each pixel of remaining pixels in the top-view image into three-dimensional point cloud data of each pixel based on the depth estimation value of each pixel, wherein the three-dimensional point cloud data of each pixel are three-dimensional coordinates of each pixel in a camera coordinate system;
• calculating a normal vector of each pixel based on the three-dimensional point cloud data of each pixel;
• determining, based on the normal vector of each pixel, a plane of the crab aquaculture cage to which each pixel belongs, wherein the crab aquaculture cage comprises five planes that are the front plane, the back plane, the left plane, the right plane, and a bottom plane of the crab aquaculture cage;
• respectively determining inner wall depths at different pixels on each of the five planes based on pixel coordinates of each pixel on each of the five planes and physical dimensions of the crab aquaculture cage;
• inputting the top-view image into the deep learning based object detection algorithm to determine crab pixels corresponding to the crabs;
• determining, based on the crab pixels, an inner wall depth of a crab pixel cluster comprising a plurality of crab pixels gathering together, through calculating an average of inner wall depths of the crab pixels gathering together on each of the front plane, the back plane, the left plane and the right plane of the crab aquaculture cage;
• determining an average of inner wall depths of the pixels of the water surface that contact with the front plane, the back plane, the left plane and the right plane, as an inner wall depth of a water level line;
• calculating a difference value between the inner wall depth of the crab pixel cluster and the inner wall depth of the water level line;
• and
• in response to a determination that the difference value is less than a predetermined threshold, sending a warning signal indicating an abnormal status of the crabs to an external device.