foot on the ground. 
DIGITAL IMAGE CORRELATION 
Testing for similarity of digital images is accomplished by 
use of numerical image correlation formulas. In these 
formulas, equal sized density arrays are compared pixel for 
pixel and a coefficient is computed indicating the 
similarity of the images. Many different formulas are 
available for this purpose. The ones tested included 
euclidian distance, normalized euclidian distance, 
normalized cross correlation, and the hadamarad trans 
formation. The normalized formulas account for lens fall- 
off and photo processing inconsistencies by subtracting 
the mean density of the array from the individual elements. 
This allows conjugate imagery having systematic density 
differences to be correlated as long as the relative con 
trast is the same. After testing it was determined that 
the normalized cross correlation coefficient yielded the 
best results and was therefore used in the development of 
the automated system. Equation 1 shows the form of the 
normalized cross correlation coefficient. In this equation 
A and B are the i,j th elements of the two arrays being 
compared and A and B are the mean densities of the arrays. 
n m 
(1) 
C 
The value of this coefficient ranges from -1 to +1 with +1 
indicating a perfect match. For our purpose it was re 
scaled to a range of 0 to 200 with lower values indicating 
better correlation. 
In order to find the location in the photo of the desired 
image array, referred to as the target array, the target 
must be compared at all possible locations in a much 
larger search array. This is accomplished by lagging the 
target array through the search array in a systematic 
fashion with a coefficient being computed for each lag 
position. The minimum coefficient thus obtained indicates 
a best match to the target. This coefficient is tested 
against a threshold value to see if the match is valid. 
This is necessary since the target may not fall within the 
search array and the minimum coefficient does not always 
indicate an acceptable match. Testing the correlation 
algorithm showed that values below approximately 40 
indicated significant correlation with values less than 
20 showing very strong correlation. 
Due to the large number of computations necessary to 
compute all of the correlations possible within the search 
array, a systematic method of lagging the target array was 
devised which allows corrections to be added to the coe 
fficient at the previous lag position. The target is 
shifted one row or column at a time with correction terms