基于CUDA计算GLCM特征值和SVM的织布疵点检测

摘要

针对当前织布疵点检测的准确率和实时性问题,提出一种基于CUDA计算灰度共生矩阵特征值和支持向量机的检测算法;该算法借助GPU基于CUDA架构计算4个方向灰度共生矩阵各自的4种特征值组成16维特征向量输入训练完成的支持向量机模型,实现对各种类型疵点图像和无疵点图像的分类检测.实验结果表明,该算法系统在准确率和实时性上都能满足工业生产的需求.%Focusing on the accuracy and real-time online problem of fabric defect detection,a detection algorithm based on features of gray level co-occurrence matrix calculated by cuda and support vector machine is proposed. In the algorithm,the six-teen-dimensional feature vector which contains four kinds of feature of gray level co-occurrence matrix of four directions calculated by cuda with the help of GPU is input to the trained support vector machine to classify the fabric images,some of which contain de-fects and others of which do not contain them.The experiment results show that the algorithm system can meet the needs of industrial production on the accuracy and real-time performance.