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Si3N4 Ceramic Ball Surface Defects’ Detection Based on SWT and Nonlinear Enhancement
Mathematical Problems in Engineering ( IF 1.430 ) Pub Date : 2021-09-14 , DOI: 10.1155/2021/4922315
Dongling Yu 1 , Huiling Zhang 1 , Xiaohui Zhang 1 , Dahai Liao 1 , Nanxing Wu 1
Affiliation  

In order to improve the detection accuracy and efficiency of silicon nitride ceramic ball surface defects, a defect detection algorithm based on SWT and nonlinear enhancement is proposed. In view of the small surface defect area and low contrast of the silicon nitride ceramic ball, a machine vision-based nondestructive inspection system for surface images is constructed. Sobel operation is used to eliminate the nonuniform background, and the silicon nitride ceramic ball surface image is decomposed by SWT. And frequency-domain index low-pass filtering is used to modify the decomposition coefficients, and an adaptive nonlinear model is proposed to enhance defects; finally, the image is reconstructed and segmented by the stationary wavelet inverse transform and the dynamic threshold method, respectively. The enhanced algorithm can effectively identify surface defects and is superior to traditional defect detection algorithms.

中文翻译:

基于SWT和非线性增强的Si3N4陶瓷球表面缺陷检测

为了提高氮化硅陶瓷球表面缺陷的检测精度和效率,提出了一种基于SWT和非线性增强的缺陷检测算法。针对氮化硅陶瓷球表面缺陷面积小、对比度低的问题,构建了一种基于机器视觉的表面图像无损检测系统。采用Sobel运算消除不均匀背景,SWT分解氮化硅陶瓷球表面图像。并采用频域指标低通滤波修正分解系数,提出自适应非线性模型增强缺陷;最后分别采用平稳小波逆变换和动态阈值法对图像进行重构和分割。
更新日期:2021-09-14
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