A golden-template self-generating method for patterned wafer inspection

Abstract

This paper presents a novel golden template self-generating technique for detecting possible defects in periodic two-dimensional wafer images. A golden template of the patterned wafer image under inspection can be obtained from the wafer image itself and no other prior knowledge is needed. It is a bridge between the existing self-reference methods and image-to-image reference methods. Spectral estimation is used in the first step to derive the periods of repeating patterns in both directions. Then a building block representing the structure of the patterns is extracted using interpolation to obtain sub-pixel resolution. After that, a new defect-free golden template is built based on the extracted building block. Finally, a pixel-to-pixel comparison is all we need to find out possible defects. A comparison between the results of the proposed method and those of the previously published methods is presented.

Automatic Detection of Texture-defects using Texture-periodicity and Jensen-Shannon Divergence

“…Methods that are found in literature for the inspection of patterned texture images include the traditional image subtraction methods [10][11][12], the method of golden image subtraction (GIS) [5], the method of wavelet-preprocessed golden image subtraction (WGIS) [5], the method of Direct-Thresholding (DT) based on wavelet transform [5], the Bollinger Bands method [6], the Regular Bands method [3], the Local Binary Pattern (LBP) method [7], and the motif-based methods [4,8,9].…”

“…Pixel-to-pixel comparison between the input image and the reference or template image, which is based on an assumed threshold, helps in identifying the defects. Xie and Guan presented a similar method, wherein the building block needed for constructing a reference image is extracted based on linear interpolation [12]. However, when the defect size in the image is too large, the building block constructed based on the methods suggested in [11,12] can never be a good estimate of the true value.…”

Defect detection in periodic patterns using a multi-band-pass filter

“…The method not only provides an inspection performance identical to other methods, but it also saves a large amount of computational time. Besides, the proposed spatial filter is also superior to the die-to-die method [8] that requires 9 + 9 real number multipliers for linear interpolation in defining the building blocks and building a defect-free image. The method can thus immensely benefit applications for AOI and AVI.…”

“…Most existing approaches for defect inspection in periodic patterns can be divided into three main classes: (1) template matching [1][2][3][4][5][6][7][8][9][10][11][12][13]; (2) neural networks [14][15][16][17][18][19][20]; and (3) filter approaches [21][22][23][24][25][26][27][28][29][30][31][32][33]. A few other studies have reported approaches other than the abovementioned [34].…”

“…The traditional template matching method uses an external golden template created by the image registration and segmentation process to discriminate defects [2][3][4]. An alternative approach is the die-to-die inspection method [4][5][6][7][8][9][10][11][12] that can be considered as a special form of the template-based approaches that have been adopted in many industrial applications. This approach is well-known for its simplicity and computational efficiency.…”