Template-Set Approach to VLSI Pattern Inspection

Chae, Soo-Ik; Walker, James T.; Dameron, David H.; Fu, Changlin; Meindl, J.D.

doi:10.1117/12.937868

Cited by 2 publications

(1 citation statement)

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“…pixel-by-pixel comparisons) and local-property inspection methodologies (i.e. local-pattern template matching) [15]. This limitation to black and white image processing prevents identification of certain classes of defects, and it is clear that inspection can be greatly enhanced by the use of color vision.…”

Section: Introductionmentioning

confidence: 99%

<title>Use of color in integrated-circuit inspection</title>

Barth¹,

Beni

Hackwood

1990

SPIE Proceedings

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Color can play a very important role in the in-process, in-situ inspection of integrated circuit structures. Optical interference effects caused by thin films give colors that are characteristic of film thicknesses. For these optically transparent thin films (such as silicon dioxide) that make up the IC structures, interference effects take place when white light impinges upon the wafer. As a result, the features on an IC wafer are inherently colorful. We take advantage of this color dimension in our automated IC wafer inspection system in three ways: 1) Since the colors of the IC patterns are characteristic of film thickness, it is possible to measure analytically the varying thin film thicknesses based on their colors. The relationship between the measured color and thin film thickness has been determined empirically and also modeled analytically. We can rapidly (< 100 msec) measure oxide and other thin film thicknesses based on color in the range of 390A -i0,030A with 30A accuracy. 2) Since the patterns on an integrated circuit have distinct colors, it is possible to segment the images based on their color attributes. During inspection, we employ a color clustering method along with a unique multiple-valued connectivity algorithm to perform rapid, robust segmentation of IC pattern images.3) Since the majority of IC wafer inspection systems today do not use color vision, they miss an entire class of color defects that occur during various stages of the IC manufacturing process. It has been shown that a number of these defects are detectable solely in color, rather than in grayscale images. Therefore, color allows us to detect a larger number of potential defects than systems that employ grayscale imaging alone.

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Section: Introductionmentioning

confidence: 99%