基于SMO算法的皮带撕裂红外图像检测方法

更新时间:2023-07-13 20:41:39 阅读: 评论:0

teacher是什么意思基于SMO算法的皮带撕裂红外图像检测方法
作者:徐善永 黄友锐 冯涛 韩涛
来源:《现代电子技术》2020年第11期pets3
龙娃主题曲
英语测试题
        摘; 要: 针对运煤皮带经常性的纵向撕裂问题,考虑到煤码头复杂环境引起的检测不精确性,提出基于序列最小最优化(SMO)算法的红外图像检测方法。由于煤码头存在着
悉尼科技大学设湖北奖学金大量的水雾和粉尘,将在很大程度上影响图像的提取和处理。通过获取运煤皮带的红外图像,采用SMO算法构建决策模型并对红外图像进行分割。由实验效果图可得,分割效果良好,辨识度高,并从检测精度和分割时间两个角度出发,通过对比BP神经网络算法、SVM算法和SMO算法,表明SMO算法不仅预测精度高,而且实时性好,能够满足皮带撕裂图像检测的诊断要求。
        关键词: 红外图像检测; 运煤皮带; 纵向撕裂; SMO算法; 图像分割; 决策模型
淘宝培训学校        中图分类号: TN911.73⁃34; TD634; ; ; ; ; ; ; ; ; ;文献标识码: A; ; ; ; ; ; ; ; ; 文章编号: 1004⁃373X(2020)11⁃0037⁃04
某人的英文brainchild        SMO algorithm bad infrared image detection method for belt tearing
        XU Shanyong, HUANG Yourui, FENG Tao, HAN Tao
变形金刚 英文        (School of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan 232001, China)apparel
        Abstract: In view of the frequent longitudinal tearing of coal conveyor belts, an infrared image detection method bad on quential minimal optimization (SMO) algorithm is propod by taking account of the detection inaccuracy caud by complex environment of coal terminal. There is a large amount of water mist and dust in the coal terminal, which will greatly affect the image extraction and processing. Therefore, by acquiring the infrared image of the coal belt, the decision⁃making model is built and the infrared image is gmented with the SMO algorithm. It can be en from the experiment effect pictures that the gmentation results are good and the recognition degree is high. In addition, the BP neural network algorithm, SVM (support vector machine) algorithm and SMO algorithm are compared in the aspects of detection accuracy and gmentation duration. It shows that the SMO algorithm has not only high prediction accuracy, but also a fine real?time performance. Therefore, it can meet the diagnostic requirements of image detection for coal conveyor belt tearing.

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