基于纹理特征和改进VGG的家蚕蛹雌雄识别方法  

A recognition method for female and male pupae of the domestic silkworm,Bombyx mori based on texture features and improved VGG

作　　者：孙卫红 陈颖 邵铁锋 梁曼[1,2] SUN Wei-Hong;CHEN Ying;SHAO Tie-Feng;LIANG Man(College of Mechanical and Electrical Engineering,China Jiliang University,Hangzhou 310018,China;Cocoon and Silk Quality Inspection Technology Institute,China Jiliang University,Hangzhou 310018,China)

机构地区：[1]中国计量大学机电工程学院,杭州310018 [2]中国计量大学茧丝绸质量检测技术研究所,杭州310018

出　　处：《昆虫学报》2024年第6期839-849,共11页Acta Entomologica Sinica

基　　金：国家市场监管总局科技计划项目(S2021MK0217);浙江省公益技术应用研究项目(LGG20E050014)。

摘　　要：【目的】针对蚕种培育中人工分蛹效率低且易受到主观因素影响的问题,提出一种基于纹理特征和改进VGG的家蚕Bombyx mori蛹雌雄识别方法。【方法】利用透射变换矫正蚕蛹方向,截取家蚕蛹头尾图,以B通道图作为轮廓提取的基础,通过道格拉斯-普克(Douglas-Peucker, DP)算法,分析轮廓复杂性从而识别并获取家蚕蛹尾部图;采取掩膜消除背景干扰,通过多通道的特征融合图加强纹理信息;对Inception模块进行改进,将残差网络与改进后的Inception模块加入VGG模型中;利用数据增强技术扩充数据集;以精确率(precision)、召回率(recall)、精确率和召回率的调和平均F1分值以及准确率(accuracy)作为评价指标,分别对3种输入图片以及4种识别模型进行评估对比。【结果】结果表明,特征融合图在改进VGG模型上的家蚕雌蛹的精确率、召回率和F1分值分别为98.017%, 94.794%和96.375%,雄蛹的精确率、召回率和F1分值分别为95.342%, 98.231%和96.762%,识别家蚕雌雄蛹的准确率为96.580%。特征融合图识别家蚕雌雄蛹的准确率比原始灰度图的提升了18.093%,改进VGG识别家蚕雌雄蛹的准确率比原始VGG的提升了2.257%。【结论】基于纹理特征和改进VGG的家蚕蛹雌雄识别方法能降低人工劳动时间,为实现家蚕蛹雌雄自动分拣提供基础。【Aim】Aiming at the low efficiency of manual sorting pupae in silkworm breeding and the susceptibility to subjective factors,a recognition method for female and male domestic silkworm(Bombyx mori)pupae based on texture features and improved VGG was proposed.【Methods】The transmission transformation was used to correct the direction of B.mori pupae,and the head and tail images of B.mori pupae were intercepted.B-channel image was used as the basis of profile extraction.The profile complexity was analyzed by Douglas-Peucker(DP)algorithm to identify and obtain the tail image of B.mori pupae.The background interference was eliminated with a mask and the texture information was enhanced by multi-channel feature fusion image.The Inception module was improved,and the residual network and the improved Inception module were added to the VGG model.The data set was expanded by data enhancement technology,and three kinds of input images and four recognition models were evaluated and compared by using the precision,recall,harmonic average F 1-score of the precision and recall,and accuracy as the evaluation indexes.【Results】The results showed that the precision,recall and F 1-score of the improved VGG model of feature fusion images for female pupae of B.mori were 98.017%,94.794%and 96.375%,respectively,while those for male pupae were 95.342%,98.231%and 96.762%,respectively,and the accuracy in identifying female and male pupae of B.mori was 96.580%.The accuracy of the feature fusion image in identifying female and male pupae of B.mori was 18.093%higher than that of the original gray scale image,and the accuracy of the improved VGG in identifying female and male pupae of B.mori was 2.257%higher than that of the original VGG.【Conclusion】The recognition method for female and male B.mori pupae based on texture features and improved VGG can reduce the labor time,providing a basis for the realization of automatic sorting of female and male pupae of B.mori.

关 键 词：蚕蛹 性别 纹理特征 道格拉斯-普克算法 Inception模型 VGG网络 

分 类 号：Q969[生物学—昆虫学]