Paper
1 June 1990 Quantitative measures for surface texture description in semiconductor wafer inspection
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Abstract
The automation of visual inspection in semiconductor wafer processing is a very challenging task. In this paper we address the automatic description and measurement of surface textures in semiconductor wafers. Texture plays a critical role in inspecting surfaces that are produced at various stages in the inspection of semiconductor devices. In this paper we describe a novel scheme to characterize surface textures that arise in semiconductor wafer processing. The emphasis in our scheme is on quantitative measures that allow for accurate characterization of surface texture. The fractal dimension is a quantitative measure of surface roughness, and we have developed an algorithm to automatically measure this. We also present an algorithm to compute the orientation field of a given texture. This algorithm can be used to characterize defects such as 'orange peel'. Furthermore, we have used the qualitative theory of differential equations to devise a symbol set for oriented textures in terms of singularities. An algorithm has been devised to process an image of a defect and extract qualitative descriptions based on this theory. We present the results of applying our algorithms to representative defects that arise in semiconductor wafer processing.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Ravishankar Rao and Ramesh C. Jain "Quantitative measures for surface texture description in semiconductor wafer inspection", Proc. SPIE 1261, Integrated Circuit Metrology, Inspection, and Process Control IV, (1 June 1990); https://doi.org/10.1117/12.20043
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Cited by 7 scholarly publications.
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KEYWORDS
Inspection

Semiconducting wafers

Image segmentation

Fractal analysis

Differential equations

Coherence (optics)

Evolutionary algorithms

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