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Highlights

A 3D reconstruction algorithm is proposed to determine the snakehead area.

Abstract. A whole-skin peeling system for a snakehead is designed in this article. The snakehead photos are taken from multiple angles and are first filtered to extract the image features, before reconstructing the sparse model. Then, the characteristic parameters of the snakehead are determined through the point cloud coordinates, and dense reconstruction is carried out based on sparse points. The accurate three-dimensional spatial coordinates of the snakehead are obtained by the octree algorithm and Poisson surface reconstruction algorithm. Based on the triangular meshing algorithm, the skin area of a snakehead is calculated to determine whether the snakehead meets the peeling conditions. A trained Faster Region Convolutional Neural Network (R-CNN) is used to identify the fin position on the snakehead reconstruction model and program the cutting route on the fish neck, while the cutting route of the fish belly is determined by selecting the area of the excretory hole through the ROI region of interest. Finally, the designed mechanical structure is used to peel the whole skin of the snakehead. The experimental results show that the maximum fluctuation rate of the snakehead area calculated by the proposed three-dimensional reconstruction algorithm is less than 4.0%, and the accuracy reaches 87.3%. The average precision (AP) for the determination method of the fish neck cutting position on the snakehead is 90.89%, which proves the effectiveness and feasibility of this method. The present results provide useful technical support for automating fish whole-skin peeling and shedding light on the accurate determination of the surface area and the extrication of the morphological feature parameters of other organisms.