Interface Defect Detection of Semiconductor Thin Film Materials Based on Sparse Imaging
Detecting interface defects of semiconductor thin film materials under complex backgrounds is chal-lenging.In order to accurately detect interface defects,a method for detecting defects in the interface of semiconductor thin film materials was proposed based on sparse imaging.Firstly,the two-dimensional images of the interface of sem-iconductor thin film materials were scanned and collected.Then,wavelet decomposition was applied to the interface with noise thus obtaining sub-images with different frequency bands.Under the condition that the low-frequency im-age remained unchanged,corresponding templates were selected to filter high-frequency images.After filtering,the high-frequency and low-frequency images were combined to obtain a denoised image.Meanwhile,the defect of the film material interface was located by machine vision.Meanwhile,the feature of the defect region was extracted from the position Moreover,feature parameters were corrected by sparse imaging,and ultimately,defect detection in the in-terface of semiconductor thin film materials was completed.Simulation results show that the proposed method can ob-tain more accurate test results with shorter processing time,which meets the requirements for efficient and high-preci-sion tests.
Sparse imagingSemiconductorThin film materialsInterface defect detectionWavelet decomposition
NETL
NSTL
万方数据
维普
