An Empty Bottle Intelligent Inspector Based on Support Vector Machines and Fuzzy Theory
An Empty Bottle Intelligent Inspector Based on Support Vector Machines and Fuzzy Theory
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DOI：
10.1109/wcica.2006.1713895
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发表时间：
2006-10
期刊：
影响因子：
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通讯作者：
Huan-jun Liu;Yao-nan Wang;Feng Duan
中科院分区：
文献类型：
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作者：
Huan-jun Liu;Yao-nan Wang;Feng Duan
本文研究了基于机器视觉代替人工检测的空瓶智能检测系统。文中详细阐述了该系统的结构。文中还介绍了从图像中提取特征的方法。在提取特征后，采用模糊支持向量机作为分类器。同时提出了一种基于优化算法的遗传算法来确定模糊支持向量机的参数，保证了模糊支持向量机具有良好的分类能力。实验表明，利用该方法对空瓶进行检测，准确率可达96%以上
This text studies empty bottle intelligent inspector based machine vision instead of manual inspection. The system structure is illustrated in detail in this paper. The text also presents the method to extract features from images. After extracting feature, the fuzzy support vector machines are used as classifier. A genetic algorithm based on optimization algorithm is simultaneously proposed to confirm the parameters of the fuzzy support vector machines, ensuring that the fuzzy SVMs have good classification ability. The experiments demonstrate that using this method to inspect empty bottles, the accuracy rate may reach above 96%