天津农学院学报 ›› 2023, Vol. 30 ›› Issue (4): 53-57.doi: 10.19640/j.cnki.jtau.2023.04.010

• 研究与简报 • 上一篇    下一篇

视觉识别的生活垃圾分类系统设计

马含章, 王淼鑫, 钟拼扬, 刘华通信作者, 常若葵, 董晋峰   

  1. 天津农学院 工程技术学院,天津 300392
  • 收稿日期:2022-05-12 出版日期:2023-08-31 发布日期:2023-11-01
  • 通讯作者: 刘华(1977—),女,高级实验师,硕士,主要从事分析仪器维护的理论研究与实践、电力电子与电气传动方向研究以及智能农机装备设计。E-mail:41599386@qq.com。
  • 作者简介:马含章(2000—),女,本科在读,主要从事测控技术与仪器方面的研究。E-mail:1105405107@qq.com。
  • 基金资助:
    天津农学院教改项目(2021-A-43); 教育部高等教育司产学合作协同育人项目(202102507002)

Design of garbage classification system based on visual recognition

Ma Hanzhang, Wang Miaoxin, Zhong Pinyang, Liu Hua, Chang Ruokui, Dong Jinfeng   

  1. College of Engineering and Technology, Tianjin Agricultural University, Tianjin 300392, China
  • Received:2022-05-12 Online:2023-08-31 Published:2023-11-01

摘要: 为解决市民缺乏垃圾分类专业知识,不能准确判断垃圾种类,导致垃圾分类效果不够理想的问题,设计一款能自主识别垃圾种类并完成分装的垃圾分类系统。该系统采用视觉识别技术,将采集到的图片与训练好的模型进行比对,通过算法计算出相似度最高的垃圾类型,并将结果发给控制中心,控制中心根据垃圾种类控制投放模块工作。经测试,该系统目前可识别的范围包括全部四个大类垃圾中常见的十余种垃圾及其不同形态,识别准确率约为78%。

关键词: 智能垃圾分类, 垃圾分类数据集, 视觉识别, 投放系统

Abstract: In order to solve the problem that citizens, lack professional knowledge of garbage sorting , can not accurately judge the type of garbage, which leads to the unsatisfactory effect of garbage sorting, this paper introduces a system that can independently identify the type of garbage. This system uses visual recognition technology to compare the collected images with the trained model, calculates the garbage types with the highest similarity through the algorithm, and sends the results to the control center. The control center works according to the garbage type control delivery module. After testing, the range of recognition includes more than ten kinds of garbage common in all four categories and their different forms, and the recognition accuracy is about 78%.

Key words: intelligent garbage classification, garbage classification data set, visual recognition, delivery system

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