Multi-scale decomposition enhancement algorithm for surface defect images of Si₃N₄ ceramic bearing balls based on stationary wavelet transform

Abstract

In order to improve the detection efficiency and image quality of Si 3 N 4 ceramic bearing balls surface defects, digital image processing technology is used to analyse the information characteristics of Si 3 N 4 ceramic bearing balls surface. A multi-scale decomposition enhancement algorithm for surface defect images of Si 3 N 4 ceramic bearing balls based on the stationary wavelet transform is proposed. By building the surface defects detection system of Si 3 N 4 ceramic bearing balls, the image enhancement program based on stationary wavelet transform with index low-pass filtering and nonlinear transform enhancement is designed. Finally, the effectiveness of the algorithm is verified by experiments. The experimental results show that the algorithm is applied to the surface defects image of Si 3 N 4 ceramic bearing balls can effectively weaken the background noise and surface grinding texture, and enhance the contrast between defects and background clearly. In addition, the binary image is obtained by an adaptive threshold binary algorithm. After removing the tiny points by morphological opening operation, the defects are accurately and completely segmented, and then the Canny operator is used for edge detection to extract the edge contour of defects. When the decomposition level is set to 3, the average calculation time is 0.88 s, which are relatively short and have sufficient precision, and the algorithm can be extended to other kinds of ceramic ball surface damage detection.

Offline handwritten Tai Le character recognition using wavelet deep convolution features and ensemble deep variationally sparse Gaussian processes

“…The WD feature obtains multiple wavelet sub images by multilevel decomposition of the original images, which can increase the degree of difference between different character images. The deep convolution feature can further obtain high-level semantic information and character contour information as the depth increases (Yu et al 2020). This method solves the problem of a large number of similar characters in offline handwritten Tai Le characters.…”

Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

“…Define the two-dimensional smoothing function, use its first-order partial derivatives in the horizontal and vertical directions as the two fundamental wavelets of the image transform, and then define the convolution of the scaling wavelets of the fundamental wavelets in the two directions with the image as the horizontal and vertical components of the wavelet transform, respectively, and find out the modulus and amplitude angle of the wavelet transform, and define the modulus maximum of the wavelet transform along the phase angle direction as the image edge. The two-dimensional smoothing function is shown in Equation (1).…”

“…Due to the hard and brittle nature of ceramics, their poor thermal conductivity and wear resistance make them very difficult to machine. Currently, ceramic processing is mainly based on grinding with diamond tools (mainly grinding wheels) [1]. The processed surface generally has textural characteristics related to the processing method as well as broken, scratched, cracked, and other damage, and the geometric structure of these rough surfaces has a close relationship with many surface features, such as the following: in the mechanical industry, the surface shape characteristics of the processing, not only on the entire system of contact stiffness, contact strength, friction and wear, and the nature of the fit, as well as transmission accuracy, have a great impact; thus, in the electronics industry, the roughness of the silicon wafer surface has an increasing impact on the thin film capacitance and thin film resistance in the integrated circuit, thus affecting the performance and yield of the entire integrated circuit device; in the biomedical manufacturing industry, the surface morphology of artificial joints and other artificial organs will directly affect the flexibility and life of the joints; in the aerospace manufacturing industry, the surface shape of optical components, even if only a small microscopic bump, will cause light scattering and make the performance of the optical system worse, thus affecting the performance of the whole system [2].…”

The algorithm for extracting surface defects from ZrO2 ceramic bearing balls using shearlet transform image enhancement

“…3 In the process of fabricating ZrO 2 ceramic bearing balls, due to the influence of materials, production environment, and process, some ZrO 2 ceramic bearing balls' surfaces will inevitably appear with scratches, pits, cracks, and other defects. 4 The surface defects will seriously reduce the strength of the balls and shorten the service life of ZrO 2 ceramic bearings. 5,6 With the rapid development of the manufacturing industry, the performance requirements of ZrO 2 ceramic bearings are constantly improving.…”