In this paper, aiming at the difficulty in counting the frequency of fish tail beats in aquaculture practice, a computer vision-based method for measuring the frequency of swimming fish tail beats is proposed. The camera is used to obtain video, the binary image containing only fish is obtained after background subtraction and binarization and then thinned to obtain the median line in the direction of the spine of the fish, the corner detection algorithm is used to extract the head feature points, tail feature points and the feature points on the spine curve of the fish body, and the curvature of the fish body is calculated through the feature points. The image with the curvature close to zero is manually selected, and the curvature value is calculated using the algorithm. The magnitude and variance of the statistical error are counted to determine the curvature threshold. The method is verified by using Larimichthys crocea as the experimental object. Comparing the results of algorithm measurement and manual counting, it is found that the accuracy reaches 91.7%, which can better measure the number of tail beats. Compared with the method based on distance, the algorithm has less fluctuation when measuring the image with larger curvature, and is more suitable for the measurement of frequency of tail beats.