Study on Surface Characteristics of Linear Traces Based on Wavelet Transform
Bingcheng Wang, Jing Chang · 2019
Based on analysis of wavelet transformation with excellent time-frequency local microscopic characteristics, the wavelet transformation technique is applied to the analysis of surface features of linear traces. A batch of linelike trace samples made with the same instrument are selected to select two samples with the same trace surface contour curve but with slight differences. Then two sets of data of the two samples are collected for noise reduction. By comparing the curve and fractal dimension drawn by the original data and the noise-reduced data, it is shown that the interference of "noise" caused by pollution in the process of acquisition and dispersion is eliminated, and the reconstructed measuring contour curve maintains the original statistical fractal characteristics, the difference points are reduced and the essential characteristics are more obvious. At the same time, the difference of fractal dimension between the two samples calculated from the denoised data is small. Therefore, the wavelet transformation technology can eliminate the non-essential differences between the scene trace and the sample trace, and highlight its essential characteristics. It provides a new method to solve this problem of long-term confusion inspectors.