Method and apparatus for measuring feature dimensions using controlled dark-field illumination

A method and apparatus for measuring feature dimensions uses selective dark-field illumination to illuminate a target from a single direction at a low angle to the plane of the target. Opposing edges of the target elements are distinguished and captured in separate images. The images are filtered using a Gaussian convolution operator and a Laplacian operator. The signs of the filtered images are correlated at various offsets. The relative displacement of the images which produces the maxium correlation value is used to calculate the average dimension of the target elements.

BACKGROUND OF THE INVENTION 
This invention relates generally to the measurement of feature dimensions, 
and specifically, it relates to the measurement of feature dimensions 
without manual intervention using dark-field illumination to distinguish 
the edges of a feature and using image processing techniques to measure 
the disparity between opposing feature edges. 
Dark-field microscopy is a technique in which an illumination source 
provides a convergent cone of light at a low angle to the plane of the 
specimen, centered on and symmetrical about the optical axis of the 
imaging system. The image is formed by collecting and focusing only that 
light which is scattered from topographic feature edges on the specimen. 
Since flat areas reflect rather than scatter, they appear dark in the 
image, while feature edges appear light. 
In the prior art, techniques are known for extracting the dimensional 
information from the images generated by dark-field microscopy without 
manual intervention. Generally, these known techniques analyze the image 
to discriminate the opposing feature edges and calculate the distance 
between the opposing edges. These techniques use either a single scan line 
from the image or the average of multiple scan lines to reduce the effects 
of high-frequency noise. Typically, a target in the shape of a single 
rectangle is scanned and the resulting data is analyzed to identify the 
opposing edges. By focusing attention on detailed analysis of the feature 
edges, however, such prior art techniques have certain inherent 
limitations. Firstly, since the information representing the details of 
the edges are carried in the high spatial frequency region of the image 
spectrum, limited and laborious techniques for high frequency noise 
reduction are required. Secondly, the results are sensitive to the details 
of the contrast formation mechanism of specific samples and tend to vary 
from one type of specimen to another or even for different specimens of 
the same type. Thirdly, the contrast formation is sensitive to the 
illumination and other parameters of the imaging equipment, such as focus, 
so that results from a single specimen will be different depending on the 
settings. 
SUMMARY OF THE INVENTION 
The present invention provides a method and apparatus for measuring feature 
dimensions using selective dark-field illumination to distinguish opposing 
feature edges and using image processing techniques to measure the 
dimension between opposing feature edges. The standard dark-field 
illumination technique is modified to illuminate a target from a single 
direction at a low angle to the plane of the target. By selectively 
illuminating the target from opposing directions, the opposing edges of 
the target elements are segregated and captured in separate images. The 
separate images are then correlated at various offsets to determine the 
relative displacement of the images which produces the maximum correlation 
value. This displacement is proportional to the average dimension of the 
target elements. 
In a typical application, this technique is used to measure critical 
feature dimensions in the manufacture of integrated circuits. The target 
is composed of elements having the same size as the smallest features of 
the integrated circuit. 
In a preferred embodiment, the images obtained by selective dark-field 
illumination are each filtered before performing the correlation. The 
filtering method used in this embodiment applies a Gaussian convolution 
operator and a Laplacian operator to the image. The signs of the filtered 
images are stored and used in the correlation.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
FIG. 1 is a schematic representation of an apparatus 10 for measuring 
feature dimensions using controlled dark-field illumination. An image 
acquisition system 12 is aimed at a target 14 contained on specimen 16. 
Image acquisition system 12 is coupled to an image processing system 18. 
Target 14 provides an artifact whose image can be analyzed to measure the 
dimensions of the features (elements) of which it is composed. 
In one application of this invention, the target is used for measuring the 
dimensions of features in integrated circuit photolithography. In the 
manufacture of integrated circuits, the critical dimensions are those of 
the minimum feature size. Therefore, for this application, the target is 
composed of elements having the same size as the smallest features of the 
integrated circuit pattern which is being printed. The target is printed 
using the same processes used to print the integrated circuit, thereby 
providing a measure of the accuracy of the processes. 
The spatial geometry of target 14 can be optimized to exploit the 
properties of the image processing technique to be described herein. This 
image processing technique operates optimally when the spatial frequency 
spectrum of the image is spread evenly throughout the band width of the 
imaging system. This condition is approximated by composing the target as 
a regular orthogonal array of potential elements, and populating the 
actual target by randomly filling 50% of the potential locations. 
Therefore, in this embodiment, the target is constructed by composing an 
array of dots with a dimension along their diameter equal to the minimum 
feature size of the integrated circuit (nominally one micron), and 
randomly placing these dots on a square grid of potential locations 2.5 
microns apart on their centers. To facilitate identification of the 
target, the elements which compose the target are placed in a four-fold 
symmetric arrangement. The resulting target is illustrated in FIG. 2. It 
will be understood, however, that there is considerable flexibility in the 
design of the target. 
Image acquisition system 12 comprises image illumination means and an image 
capture system. The illumination means may be any means for selectively 
illuminating opposing edges of the features to be measured. The particular 
image capture system is immaterial, provided it produces a digitized 
grey-level representation of the illuminated target. 
In this embodiment, image acquisition system 12 comprises an Olympus 
metallurgical microscope having a 20x field objective lens and 
illuminator, with a camera mounted on the trinocular head of the 
microscope to record the image. The camera is an RCA series TC-1005 with a 
high sensitivity Ultricon tube. A 6.7x camera eyepiece is used. 
The illumination source of this dark-field microscope normally provides a 
convergent cone of light at a low angle to the plane of the specimen, 
nominally centered on and symmetrical about the optical axis of the 
imaging system. The image is formed by collecting and focusing only that 
light which is scattered from topographic feature edges on the specimen. 
Since flat areas reflect rather than scatter, they appear dark in the 
image. FIG. 2 is an example of a conventional dark-field image. 
To provide selective dark-field illumination, the standard (360.degree.) 
dark-field illumination technique is modified, such that the uniform cone 
of light is replaced by a narrow "pencil" of light at a low angle. This 
selective illumination selects only those topographic feature edges which 
effectively scatter light from that direction. Other edges are suppressed 
in the resulting image. This technique is particularly well-suited for 
distinguishing opposing edges of the target. 
FIGS. 3a-3d illustrate schematically the selective dark field illumination 
technique. FIG. 3a is a side view of microscope 30 viewing a specimen 32 
using conventional dark-field illumination. FIG. 3b is a top view of the 
specimen 32 when illuminated from 360.degree. using conventional 
dark-field illumination. All edges, and only the edges, are visible. FIGS. 
3c and 3d are top views of the images created by selective dark-field 
illumination from opposite directions. 
In this embodiment, a "pencil" of light is approximated by inserting a 
sector-aperture in the path of the illuminator, so that most of the cone 
of illumination is blocked, but a narrow sector is allowed to pass through 
the microscope optics in the usual way. A sector angle of 60.degree. is 
used in this embodiment to produce the micrograph shown in FIG. 4, from 
the same specimen as FIG. 2. By rotating the sector-aperture by 
180.degree., illumination from the complementary direction is obtained, 
producing the image shown in FIG. 5. The image is then recorded by the 
camera, digitized, and then processed by the image processing system. 
By using selective dark field illumination, the opposing edges of the 
target are distinguished and captured in two separate images. The two 
images are then correlated at selected offsets to provide a measure of the 
average feature dimension, i.e. the average distance between opposing 
edges of the elements in the target. The offset, or relative displacement 
of the images (relative to the initial orientation of the captured 
images), which produces the maximum correlation between the images is 
proportional to the average feature dimension of the elements in the 
target. 
The accuracy of the correlation measurement can be improved substantially 
by filtering the images to enhance their low frequency (clustering) 
structure and attenuate the high frequency (detailed) information. 
Although many different types of filters may be employed for this purpose, 
in the preferred embodiment a Gaussian convolution operator is used. The 
Gaussian convolution employed is a two dimensional Gaussian which 
functions to low pass filter the image in a way that attenuates high 
spatial frequencies, while preserving the geometric structure at lower 
spatial frequencies. The size of the Gaussian operator controls the scale 
at which structure remains in the filtered image. A Laplacian filter is 
also employed, to detect the locations in the image where local maxima in 
the rate of brightness change occur. These locations correspond closely 
with the locations where the Laplacian has a zero value. Only the signs of 
the Laplacian are stored and used (in binary form) in the correlation, 
thereby effectively comparing the zero crossings of the Laplacian of the 
convolved signals. 
Because the order of application of the Laplacian and Gaussian operators 
does not affect the result of the filtering operation, either the 
Laplacian or the Gaussian operator may be applied first. Although a 
suitably programmed general purpose computer can be used to apply the 
Laplacian and Gaussian convolution operator to the digitized image and 
take the sign of the result, the image processing means of the preferred 
embodiment utilizes specialized hardware for this purpose. A method and 
apparatus for performing the Laplacian of Gaussian filtering is described 
in the copending commonly assigned U.S. patent application entitled 
"SYSTEM FOR EXPEDITED COMPUTATION OF LAPLACIAN AND GAUSSIAN FILTERS AND 
CORRELATION OF THEIR OUTPUTS FOR IMAGE PROCESSING", Ser. No. 888,535, 
filed Jul, 22, 1986 now abandoned. That application, which is hereby 
incorporated by reference, describes in detail the method and apparatus 
employed in this embodiment to perform these calculations. The results of 
applying this technique to the images of FIGS. 4 and 5 are shown in FIGS. 
6 and 7, respectively. The Gaussian convolution was performed with an 
operator having a center diameter of 16 pixels. In FIGS. 6 and 7, the 
black areas 62, 72 represent the positive sign and the white areas 64, 74 
represent the negative sign. 
After the images have been filtered using either the above-described 
process or some other desired process, the filtered images are correlated 
with each other. The method and apparatus described in the 
above-referenced patent application are used by the image processing means 
of this embodiment to perform binary area correlations to compare the 
relative position of the sign areas (the sign of the Laplacian of Gaussian 
convolution in binary form) of FIGS. 6 and 7. The system described in that 
patent application automatically performs the correlation using various 
offsets of the two digitized filtered images. The relative displacement of 
the two which results in the highest correlation may be determined by 
making as many correlation measurements as desired. 
FIG. 8 is a graph 80 of a cross-correlation of FIGS. 6 and 7, obtained by 
shifting the images in a single direction (represented by the horizontal 
axis 82) one pixel at a time. The direction of shifting is defined by the 
dimension to be measured, that is, the dimension between the opposing 
edges captured in the two images. There is a single peak 84, and the 
roll-off of correlation with displacement is relatively smooth and linear, 
which allows sub-pixel interpolation to measure relative displacement with 
accuracy and precision. To obtain more data and improve accuracy even 
further, the correlation may be extended in an additional orthogonal 
direction to plot a correlation surface. The location (on the horizontal 
axis) of the peak of the resulting cone is then determined using the 
technique described in the above-referenced patent application, or other 
techniques known in the art. 
The invention has applications beyond the example of measuring critical 
feature dimensions in integrated circuits. The technique is applicable in 
any field where directional illumination can select opposing edges of the 
specimen whose dimensions are required. The specimen must have topographic 
relief to form the image contrast when illuminated from a low angle. If 
the topographic relief is in a material transparent to the illumination, 
then the opposing edges will exhibit only partial segregation when 
selectively illuminated, because some light will be scattered by the 
"ghost" edge. This condition results in a measured feature size that is 
small by a factor of (a-b)/(a+b), where a and b are respectively the 
integrals of intensity under the illuminated edge and the ghost edge. This 
bias can be compensated for to the extent these relative weights are 
known. 
Although the circular dots used as target elements in this embodiment 
produced good results, it may be preferable in some applications to apply 
a compensating factor to the displacement measurements to account for the 
distribution of light around the feature circumference. Obviously, the 
technique is also applicable to features bounded by parallel straight 
edges, such as rectangles or squares, since this provides the most direct 
relationship between image correlation displacement and physical feature 
size. 
In summary, selective dark field illumination is used to distinguish and 
segregate opposing edges of features in separate images, and these images 
are correlated to measure the feature size (displacement between the 
edges). This technique renders it feasible to use complex patterns of 
elements for measuring average feature dimensions. These patterns provide 
more data for a particular target area and camera field than the 
single-element rectangular target used in the prior art. These patterns 
can be adapted for a particular image processing technique to compensate 
for noise and distortion from the image acquisition system. When a pattern 
with low spatial frequency content is used with the low frequency image 
processing techniques described herein, accurate, reproducible results are 
obtained. By discarding some of the high frequency information, while 
retaining some of the low frequency information, the measurement is 
relatively insensitive to small distortions and high frequency noise. 
The preceding has been a description of the preferred embodiment of the 
invention. Although specific details have been provided with respect to 
the preferred embodiment, these details should be understood as being for 
the purpose of illustration and not limitation. The scope of the invention 
may be ascertained from the appended claims.