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.
This paper presents a novel technique for detecting possible defects in two-dimensional wafer images with repetitive patterns using prior knowledge. It has a learning ability that is able to create a golden block database from the wafer image itself, modify and refine its content when used in further inspections. The extracted building block is stored as a golden block for the detected pattern. When new wafer images with the same periodical pattern arrives, we do not have to re-calculate its periods and building block. A new building block can be derived directly from the existing golden block after eliminating alignment differences. If the newly derived building block has better quality than the stored golden block, then the golden block is replaced with the new building block. With the proposed algorithm, our implementation shows that a significant amount of processing time is saved. And the storage overhead of golden templates is also reduced significantly by storing golden blocks only. Index terms:Wafer inspection -Golden template -PDI -Image-to-image reference methodGolden block 2
This paper presents a novel technique for detecting defects in periodic 2-D wafer images when there is no image database or priori knowledge. It creates golden block database from the wafer image itself and customizes its content when needed. Spectral estimation is used in the first step to derive the periods of repeated patterns in both directions. Then a building block representing the structure of the patterns is extracted. After that, a new defect-free image is built based on this building block. Finally, a pixel-to-pixel comparison is all we need to find out possible defects. The extracted building block is stored as the golden block for certain pattern. When a new image with the same periodical pattern arrives, we don't have to re-calculate its periods and building block. They can be derived directly from the existing golden block. It is a bridge between the existing self-reference methods and image-toimage reference methods.
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