基于支持向量机的彩钢玻璃色差分离技术研究

为了将彩钢玻璃中有色差的玻璃样本分离出来，提出一种利用分光测色仪检测，并与支持向量机想结合分离色差样本的方法。首先利用分光测色仪获取出样本玻璃的各采样点的CIE色度值等光学数据，建立数据样本集，然后选取特征参数及训练集并建立 SVM模型，其次选取不同类型核函数及参数进行对比实验，使模型最优化，最后利用该模型对预测集进行处理，检测并分离出有色差的玻璃样本。实验结果表明该方法可以高效准确地检测出彩钢玻璃中有色差的样本。

Research of separating color discrepancy of glass based onsupport vector machine

In order to distinguish the color discrepancy of the same color class,the method of detection based on spectrophotometer and support vector machine is proposed.First,spectrophotometer is utilized to obtain the CIE chromaticity coordinates of each point in the glasses and other optical data for establishing data sample set.Then selecting the feature parameters and establishing the training set are used for creating SVM model.Followed,the different types of kernel functions and parameters are compared to choose the best,so that they make the model optimizing.Finally, the model is used to work on the prediction set, which detecting and distinguishing the dissimilarity.The experimental results show that this method can be efficiently and accurately detected the discrepancy of color of the glass.