文献类型：期刊文献

中文题名：多种识别方式组合的智能分类垃圾桶

英文题名：Intelligent Sorting Trash Bin with a Combination of Multiple Identification Methods

作者：马新玲[1];郭兆阳[1];乐祺中[1];杨旭东[1]

机构：[1]华东理工大学机械与动力工程学院,上海200237

年份：2020

卷号：38

期号：12

起止页码：33

中文期刊名：机械与电子

外文期刊名：Machinery & Electronics

收录：CSTPCD

基金：大学生创新创业训练计划项目经费支持(201910251062)。

语种：中文

中文关键词：智能垃圾桶;垃圾分类;识别方式;投票算法;判断准确度

外文关键词：smart trash can;garbage classification;identification method;voting algorithm;judgment accuracy

摘要：设计了一款智能垃圾桶,采用高清摄像头、红外热成像仪、物相分析仪与数据处理设备,并利用机器视觉、热成像分析、物相分析等多种方式进行识别判断,与数据集对比得到垃圾分类结果。然后对多种识别方式的分类结果应用投票算法,利用控制矩阵控制各识别方式判断结果的可信度,从而计算比较得出最终判断结论。这种综合考虑多种识别方式的方法,能够有效提升垃圾分类判断的准确度。
A smart trash bin is designed,which uses a camera,infrared thermal imager,phase analyzer and data processing equipment,and uses machine vision,thermal imaging analysis,phase analysis and other methods to identify and judge,and compare with the data set to obtain the garbage classification results.Then the voting algorithm is applied to the classification results of multiple identification methods,using the control matrix to control the credibility of the judgment results of each identification method,so as to calculate and compare to reach the final judgment conclusion.This comprehensive consideration of multiple identification methods can effectively improve the accuracy of garbage classification.