×

You are using an outdated browser that does not fully support the intranda viewer.
As a result, some pages may not be displayed correctly.

We recommend you use one of the following browsers:

Full text

Title
Transactions of the Symposium on Photo Interpretation

WORKING GROUP 1
BARRETT
55
Table 3. Problems and prospects
Problem Volume of Raw Data Input (Photos)
User’s need Some Level of Auto-Screening
Typical research approach Auto Pattern Matching Devices
Major difficulty Impossibility of predicting all possible pattern variations
SDC approach Self-Learning Pattern Recognition, Self-Generated and
Dynamically Changing and Improving Master “Patterns”
We are not expecting that an automatic photo interpretation machine is
suddenly going to burst forth from our research, or from any other similar
research of which I have any knowledge. Personally, I cannot yet conceive
of such a device - of a machine equalling the capabilities of a human in
detailed photo analysis - but I do visualize a machine which can do very
rapid course screening of large amounts of photographs to determine the
presence or absence of certain gross features expected on the photography.
How far this capability may ultimately progress, I do not know. At the present
time, our’s is a research effort and certainly not a system design program.
Most present-day computers require that their input be in digital form, and
there are a number of devices available for so quantizing photographs [12, 13].
We have concentrated on processing the photos in the computer after the
initial digital input operation. Research-type test operations are now being
Fig. 1.
Operator function
OPERATOR
1
1
1
1
0
1
0
OPERATOR
1 __
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
HI
TA
1
1
1
1
1
1
1
1
1
1
1
1
0
U-
UJ
Q,
JAT
OR
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
o
z
1
HI
T E
1
1
£
.
1
1
1
-
cc
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1