Abstract:

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, we proposed the method of image inspection based on the particle analysis of mathematical morphology and fuzzy
kernel clustering. Firstly we use morphology particle analysis for the image coating surface of the aluminum, then se parallel structure characteristic of the mathematical morphology by introducing kernel function to fuzzy kernel lustering in the feature space, to achieve the purpose of quality inspection. The experimental results show that this method can achieve convergence rate 18. 4 s, classification accuracy rate can reach 91. 6%, the overall performance is better than the traditional clustering methods, and has strong robustness.

Key words: mathematical morphology, granulometry, kernel function, clustering analysis