关键词: 水下立体视觉, 视觉测量, 水下图像分割, 目标检测

Abstract:

Selection and grading of sea cucumber is an important step for underwater intelligent fishing operations. However, the size of sea cucumber cannot be accurately obtained due to refraction underthewater. So, the underwater binocular calibration method is adopted to calculate parameters of underwater camera and eliminate image distortion caused by the refraction of underwater light. On this basis, an automatic detection and size measurement method for underwater sea cucumber is proposed. Firstly, on the left correction image, the pretrained YOLOv3 detection model for sea cucumber is used to find the bounding boxes of sea cucumbers. In addition, it constructs current depth information of underwater scene by using binocular correction image. Then, a novel GrabCut-RGBD image segmentation method is constructed based on the Gaussian model of fusion color and depth information, and regions of interest with sea cucumber are separated from the background in the bounding box. Finally, by using a convex hull and rotating calipers algorithm, the optimal size measurement points are found on the segmented sea cucumber target image and using triangulation principle to realize automatic measurement of sea cucumber size. The experimental results show that the average error of the proposed method is 1.65% in the range of 0.5~1.5 m, which can fairly realize the automatic detection and size measurement of sea cucumber under the water.

Key words: underwater stereovision, vision measurement, underwater image segmentation, object detection