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| 基于透射光和反射光图像同位分割的小麦品种识别方法研究 | |
| 引用本文： | 闫宁,张晗,董宏图,康凯,罗斌.基于透射光和反射光图像同位分割的小麦品种识别方法研究[J].浙江农业学报,2022,34(3):590-598. |
| 作者姓名： | 闫宁 张晗 董宏图 康凯 罗斌 |
| 作者单位： | 1.中北大学 机械工程学院,山西 太原 0300512.北京农业智能装备技术研究中心,北京 1000943.北京农业信息技术研究中心,北京 100094 |
| 基金项目： | 国家重点研发计划(2017YFD0701205);北京市农林科学院青年基金(QNJJ202104);北京市农林科学院2021年度科研创新平台建设(PT2021-04) |
| 摘 要： | 为提高基于机器视觉的小麦品种识别准确性,本文通过透射光和反射光同位图像分割对种子颜色特征参数进行了优化提取.采用透射光图像辅助反射光图像分割的方式从种子图像中分割出胚部区域,并分别提取小麦整粒、种胚、胚乳区域的颜色特征参数.以济麦22、济麦44、京麦9、京麦11共4个品种种子作为研究对象,利用HALCON机器视觉软件获... |
| 关 键 词： | 机器视觉 小麦 品种识别 透射光 胚部 胚乳 颜色特征 |
| 收稿时间： | 2021-07-19 |
Wheat variety recognition method based on same position segmentation of transmitted light and reflected light images |
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| YAN Ning,ZHANG Han,DONG Hongtu,KANG Kai,LUO Bin.Wheat variety recognition method based on same position segmentation of transmitted light and reflected light images[J].Acta Agriculturae Zhejiangensis,2022,34(3):590-598. | |
| Authors: | YAN Ning ZHANG Han DONG Hongtu KANG Kai LUO Bin |
| Institution: | 1. School of Mechanical Engineering, North University of China, Taiyuan 030051, China 2. Beijing Research Center for Intelligent Agricultural Equipment, Beijing 100094, China 3. Beijing Agricultural Information Technology Research Center, Beijing 100094, China |
| Abstract: | A segmentation method of embryo and endosperm image based on transmitted light and reflected light at the same position of wheat seeds was proposed in order to improve the recognition accuracy of wheat varieties. In this paper, according to the characteristics of great difference in transmissibility between embryo and endosperm of wheat seed, color feature information was extracted from reflected light images and transmitted light images for modeling and analysis, the influence of transmission light characteristics and color characteristics of seed embryo and endosperm on wheat seed variety recognition were studied. Taking the four varieties of seeds of Jimai 22, Jimai 44, Jingmai 9, and Jingmai 11 as the materials, the color characteristic parameters of the seeds were obtained by using the HALCON machine vision software, and through partial least squares discriminant analysis (PLS-DA) method to establish a classification model. The results showed that after the transmission light image was used to assist the reflected light image segmentation, more seed color parameter information was fused, so that the accuracy of the four varieties of wheat seed recognition was improved. The correct rate of hybrid recognition between Jimai and Jingmai had increased from 95% of the color characteristics of seed reflected light to more than 99% of the color characteristics of transmitted light, embryo and endosperm. The hybrid recognition accuracy rate of Jimai 22 and Jimai 44 increased from 73.28% to 84.60%, and the hybrid recognition accuracy rate of Jingmai 9 and Jingmai 11 increased from 74.15% to 83.73%. The further fusion analysis of the color features contained in the image of seed embryo and endosperm through the transmitted light features can effectively improve the accuracy of wheat variety recognition. |
| Keywords: | machine vision wheat species identification transmitted light embryo endosperm color features |
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