Si3N4 Ceramic Ball Surface Defects’ Detection Based on SWT and Nonlinear Enhancement

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-...

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Bibliographic Details
Published in:Mathematical problems in engineering 2021-09, Vol.2021, p.1-9
Main Authors: Yu, Dongling, Zhang, Huiling, Zhang, Xiaohui, Liao, Dahai, Wu, Nanxing
Format: Article
Language:English
Subjects:
Algorithms
Cameras
Ceramics
Decomposition
Defects
Image enhancement
Image reconstruction
Inspection
Low pass filters
Machine vision
Noise
Nondestructive testing
Silicon nitride
Surface defects
Vision systems
Wavelet transforms
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Summary: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.
ISSN:1024-123X
1563-5147
DOI:10.1155/2021/4922315