铝型材表面喷涂质量的图像检测与研究

Image Inspection and Research of Aluminum Surface Coating Quality

针对用人眼检测铝型材表面喷涂质量效率低且容易疲劳的问题,提出了基于数学形态学颗粒分析和改进后的模糊核聚类的图像检测方案。对铝型材表面喷涂的图像进行形态学颗粒分析,利用数学形态学的并行结构特性通过核函数在特征空间中进行模糊核聚类,从而达到质量检测的目的。实验结果表明,该方法收敛速度达到18.4 s,分类准确率达到91.6%,在整体性能上超过传统的聚类方法,并具有较强的鲁棒性。

Aluminum surface coating quality in production enterprises generally inspected by human eyes.Because the human eye can easily fatigue, and detection is inefficient. In view of this kind of situation, weproposed the method of image inspection based on the particle analysis of mathematical morphology and fuzzykernel clustering. Firstly we use morphology particle analysis for the image coating surface of the aluminum, thenuse parallel structure characteristic of the mathematical morphology by introducing kernel function to fuzzy kernelclustering in the feature space, to achieve the purpose of quality inspection. The experimental results show thatthis method can achieve convergence rate 18.4 s, classification accuracy rate can reach 91.6%, the overallperformance is better than the traditional clustering methods, and has strong robustness.