Micropattern measuring method and apparatus, and recording...

Data processing: measuring – calibrating – or testing – Measurement system – Dimensional determination

Reexamination Certificate

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C382S144000, C382S145000

Reexamination Certificate

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06480807

ABSTRACT:

CROSS-REFERENCE TO RELATED APPLICATIONS
This application is based upon and claims the benefit of priority from the prior Japanese Patent Application No. 11-268711, filed Sep. 22, 1999, the entire contents of which are incorporated herein by reference.
BACKGROUND OF THE INVENTION
This invention relates to a micropattern measuring method and apparatus for measuring the pattern of a sample, and a recording medium that records a micropattern measuring program.
A method for observing a pattern on a wafer and measuring the size of the pattern, using, for example, a scanning electron microscope is widely employed for estimating a process for manufacturing semiconductor devices. In accordance with the development of device integrating techniques, various patterns are now being formed on wafers. Therefore, the conventional one-dimensional pattern measuring method cannot always detect a parameter that determines the feature of each semiconductor device. In light of this, two-dimensional measurement such as the circumferential length or the area of each device or the like has become important.
On the other hand, in accordance with the development of microfabrication of patterns, it is possible that the aberration of a lens incorporated in an exposure device will influence a lithography process for forming a pattern. In this case, for example, a deformed pattern may be obtained instead of a perfectly circular pattern. Thus, measuring the diameter of a pattern in one direction does not always provide the accurate size of the pattern. Also on this point, measuring the area of a pattern is important. Further, it is important to measure the roughness of the edge of a pattern for the estimation of, for example, a resist. In the prior art, the roughness of a pattern with a curvature, such as a hole pattern, cannot be calculated, though the roughness of a line pattern can be obtained easily.
Japanese Patent Application KOKAI Publication No. 7-27548, for example, discloses a method for solving problems as the above. In this method, an image of a hole pattern is converted to polar coordinates, and line data addition concerning the developed image is executed through 360 degrees, thereby detecting edge positions of the hole pattern. As a result, the diameter, radius, area, etc. of the hole pattern, which reflect all directions of the pattern, can be calculated.
However, in the case of a substantially perfectly circular hole pattern, components, which correspond to edge portions of the hole pattern and are included in the image of the hole pattern converted to polar coordinates, are arranged substantially linearly. On the other hand, in the case of a pattern having a high degree of roughness or an elliptic pattern, such components as the above are not arranged linearly, which may cause inaccurate detection of edge portions by line data addition. Also in this method, each edge is detected in a direction that is not perpendicular thereto, which degrades detection accuracy.
Referring to
FIGS. 1A and 1B
, the aforementioned problem caused by the method will be described in detail. In a case shown in
FIGS. 1A and 1B
, a tapered hole pattern is formed on a wafer. This pattern has a hole bottom region
101
, a hole edge region
102
corresponding to a tapered portion of the hole, and an outside region
103
. An image having portions corresponding to the regions
101
-
103
can be obtained. An edge is detected by obtaining a density distribution of the image in a direction as indicated by the arrow in FIG.
1
A. In the case of edge detection executed in an oblique direction with respect to the edge as shown in
FIG. 1A
, a density distribution with a lower contrast is obtained than in the case of edge detection executed in a direction perpendicular to the edge as shown in FIG.
1
B. Accordingly, the accuracy of detection is lower in the case shown in FIG.
1
A.
As described above, in the conventional micropattern measuring methods, edge portions are each detected, on the basis of image data, in a direction that is not perpendicular thereto, and hence the detection accuracy of the position of each edge is low.
In addition, a labeling method as another micropattern measuring method is disclosed in “Japan Atheneum 132th Committee 125th Workshop (EB Testing Symposium/1993) Document, pp. 181-186 (1993)”. Labeling indicates a method for dividing the density distribution of an image of a micropattern into a plurality of regions, using threshold values. Using the border lines of the labeled regions, the micropattern is measured. For example, this publication discloses a case of measuring a hole pattern. When measuring a hole pattern, at first, an image of the hole pattern is acquired. This image is subjected to three-valued processing concerning density. As a result of the three-valued processing, the image is divided into three regions—a hole bottom region, a hole edge region and another region. The boundary between the hole bottom region and the hole edge region is used as an edge, thereby allowing the measurement of the area or the circumferential length of each region. This method has the following problem:
FIG. 1C
shows an example of an image obtained by the above hole pattern image acquisition. Reference numeral
111
denotes a hole bottom region, reference numeral
112
a hole edge region, and reference numeral
113
an outside region. If the hole edge region
112
is partially dark as shown in
FIG. 1C
, it is difficult to execute three-valued processing. If edge detection is executed on the basis of the image shown in
FIG. 1C
, the resultant edge has a gap corresponding to a dark portion of the hole edge region, as is shown in FIG.
1
D. Thus, a desired edge cannot be obtained.
In this method, the entire image is subjected to processing. Therefore, the influence of noise cannot be avoided, with the result that edge detection cannot be executed accurately.
BRIEF SUMMARY OF THE INVENTION
It is the object of the invention to provide a micropattern measuring method, a micropattern measuring apparatus and a recording medium that records a micropattern measuring program, which enable accurate detection of edge portions of a micropattern and hence accurate measurement of the micropattern.
According to an aspect of the invention, there is provided with a micropattern measuring method, comprising the steps of: acquiring a pattern image of a sample provided with a micropattern formed thereon; creating a figure, which reflects a shape of the micropattern, on the basis of the pattern image; acquiring density distribution data on a straight line perpendicular to a tangential line of an outline of the figure; detect in g pattern edge coordinates from the density distribution data; and measuring a shape of the micropattern on the basis of the pattern edge coordinates.
According to another aspect of the invention, there is provided a micropattern measuring apparatus, comprising: a pattern image acquiring section for acquiring a pattern image of a sample; a figure creating section for creating a figure, which reflects a shape of the micropattern, on the basis of the pattern image; a density distribution data acquiring section for acquiring density distribution data on a straight line perpendicular to a tangential line of an outline of the figure; an edge detecting section for detecting pattern edge coordinates from the density distribution data; and a pattern shape measuring section for measuring a shape of the micropattern on the basis of the pattern edge coordinates.
In the present invention, a figure that reflects the shape of a pattern is created, and density distribution data on a straight line perpendicular to each tangential line of the outline of the figure is obtained, thereby detecting edge coordinates on the basis of the density distribution data. This enables edge detection at all times in a direction perpendicular to the outline of the pattern, which enhances the accurac y of the edge detection. Accordingly, shape parameters such as the area, the circumferential length, etc. of the pattern can be calculat

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