A Chinese mitten crab(Eriocheir sinensis)grading system based on Matlab image processing was designed to address the limitations of current manual grading methods for Chinese mitten crabs.First,the back and abdomen images of Chinese mitten crabs of different grades were collected at the the Taihu Lake breeding base in Huzhou City,and the collected images were preprocessed by graying,threshold segmentation,and morphology.Then,the convolutional neural network AlexNet model was used to extract the male and female features of Chinese mitten crabs,and its size was calculated using the Area Method.By selecting the weight of 10 Chinese mitten crabs and converting the pixels calculated by the system into area parameters,it was analyzed that the proportion of pixels in the back image of Chinese mitten crabs is approximately proportional to their weight.Therefore,their size characteristics can be obtained based on the calculated values of the back image.Grading was completed based on the male and female characteristics and size of Chinese mitten crabs.The experimental results show that the system has an average accuracy rate of 92.655%in recognizing male and female Chinese mitten crabs,with an average accuracy rate of 95%in size grading.
Chinese mitten crab(Eriocheir sinensis)gradingAlexNet modelMatlabimage processing
国家科技期刊平台
NSTL
万方数据
