智慧农业导刊2024，Vol.4Issue(8)：5-8,12,5.DOI:10.20028/j.zhnydk.2024.08.002
基于AlexNet模型的大闸蟹自动分级系统设计与实现
摘要
Abstract
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.关键词
大闸蟹/分级/AlexNet模型/Matlab/图像处理Key words
Chinese mitten crab(Eriocheir sinensis)/grading/AlexNet model/Matlab/image processing分类
信息技术与安全科学引用本文复制引用
黄旭,吴开龙,曾孟佳..基于AlexNet模型的大闸蟹自动分级系统设计与实现[J].智慧农业导刊,2024,4(8):5-8,12,5.基金项目
教育部人文社会科学一般项目(20YJCZH005) （20YJCZH005）
浙江省湖州市工业攻关项目(2018GG29) （2018GG29）
国家级大学生创新创业训练项目(202313287007) （202313287007）
