山东大学学报 (工学版) ›› 2024, Vol. 54 ›› Issue (3): 64-69.doi: 10.6040/j.issn.1672-3961.0.2023.099
• 机器学习与数据挖掘 • 上一篇
岳仁峰1,张嘉琦2,刘勇1*,范学忠1,李琮琮3,孔令鑫3
YUE Renfeng1, ZHANG Jiaqi2, LIU Yong1*, FAN Xuezhong1, LI Congcong3, KONG Lingxin3
摘要： 针对立体车库锈蚀检测的迫切需求,提出基于颜色和纹理特征的锈蚀检测新方法。利用高斯滤波和伽马变换解决锈蚀图片光照不均匀的问题。采用HSV(hue saturation value)色彩空间实现锈蚀的颜色特征筛选,提出基于灰度共生矩阵进行锈蚀纹理特征分析的方法,对锈蚀区域进行测量和形状分析。结合方向梯度直方图(histogram of oriented gradients, HOG)特征提取和支持向量机(support vector machine, SVM)算法实现了立体车库锈蚀检测。试验结果表明,该方法锈蚀识别准确率达到93.19%,实现了立体车库锈蚀表面的视觉检测,大大减少了外部环境的干扰。
中图分类号:
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