Quantitative study on the feeding behavior of Larimichthys crocea in live waters
This paper proposes a quantitative method on the feeding behavior of Larimichthys crocea in a live sea area to address the problem that this behavior recognition is significantly affected by the environment.This method considers Larimichthys crocea as an object and is based on the fusion of wave height information and image texture features.Research was performed on the extraction method of texture features based on GLCM using the grayscale co-occurrence matrix to calculate four quadratic statistics—energy,correlation,contrast,and inverse difference—of texture features before and after fish feeding.Texture feature methods are affected by the sea surface wave height.Therefore,the wavelet height variation example was used to study its recognition impact on texture feature methods.Artificial experience was used to determine 480 image frames,classify the feeding intensity of fish schools,and determine the recognition accuracy of a single texture feature model.The accuracy rate was 80％.The results indi-cate a recognition error in the corresponding part of the image when the wave height is greater than 0.31 cm.The possibility of this error increases with an increase in the wave height.The single texture feature model was opti-mized by introducing wave height correction parameters.Another 480 images of Larimichthys crocea were also tested before and after feeding.The sea trial results show that the accuracy of the method in the live sea area is 93％,which can effectively quantify the feeding behavior of Larimichthys crocea in the live sea area.
large yellow croakerfeeding behaviorwave heightimage texture
万方数据
维普
