A Quantitative Assessment of Freehand Drawing and Some
Suggestions for Its
Improvement as a Rock Art Recording Method
By Prof. John M. Brayer
Department of Computer Science
University of New Mexico
Albuquerque, NM, 87131 USA
Dr. Henry Walt
508 Hermosa SE
Albuquerque, NM 87108 USA
Dr. Bruno David
Department of Geography and Environmental Science Monash University
Clayton, Victoria 3168 Australia
This paper attempts to improve the quantitative understanding of one of the most frequently used
methods of rock art recording, freehand drawing. Although this method is very commonly used,
its properties are not very well understood and have not been studied quantitatively. This paper
identifies and attempts to control the objective sources of error in rock art recording by freehand
drawing. We compare the results of about 18 persons attempting to record the same panels and
we derive quantitative measures of their geometric and content inaccuracies. We conclude with
some suggestions about methods that might be used to minimize these errors.
The most frequently employed recording technique is probably photography. But freehand
drawing has been a popular rock art recording technique for many years. Some of the criteria
used to evaluate these technologies include image completeness, geometric and content accuracy
and efficiency. By image completeness, we mean recording all properties of the object even
when the glyph is very faint or difficult to decipher. Drawing has the advantage of being
inexpensive and requiring little extra equipment. Drawing allows the recorder to use his/her
interpretation to fill in details that are very faint in the original. This, of course, has both positive
and negative consequences. That is, the subjectivity of interpretive conventions can become a
help to fill in missing data but can also lead to serious errors. Faintness and superposition are
common problems in rock art that are perhaps best overcome by drawing and tracing techniques.
Drawing, sketching or drafting is likely to be inaccurate even if methods are tightly regulated.
Drawing also has the disadvantage of requiring substantially more time and skill by the recorder
than does photography. Drawing is faster than tracing but less accurate. Sketches or drawings
have another advantage over tracings in that they avoid rock contact.
We report here on the first steps we are taking in a process to quantify and improve on free-hand
drawing as a recording method. The study reported here began with 2 basic hypotheses. The first
hypothesis is that general untrained recorders do not do a very good job of recording, especially
when the subject is indistinct and relatively inaccessible. We believe that the purpose of
recording is two-fold. First, it is important for the recorder to get the general geometry right.
Secondly, the recorder should be very careful not to miss any of the details and should pay
particular attention to indistinct areas. We think that in general, recorders spend too much time
concentrating on the difficult job of getting the geometry right and often neglect the task of
studying the details and the indistinct areas.
Our second hypothesis is that recorders will do much better if given a copy of a photographic
image on a piece of paper on which they can make various corrections, additions and
annotations. In this way, they are already starting with the correct geometry and can concentrate
their whole attention on details and indistinct areas, with the distinct areas already well recorded
on the photograph. We further believe that such a recording method will be invaluable to
scholars studying the materials later, away from the site, because they have both the photo and
the annotated drawing for comparison. And the photo and the drawing are rendered in the same
II. PREVIOUS STUDIES
The methods used in this paper for registration of images are based on the technology of image
registration which is a standard method in digital image processing . To our knowledge it has
not been applied in rock art recording previously. This method is frequently used in geographic
information systems to register map data and aerial photography. One of the authors has used it
previously to detect art forgeries and in bibliographic research .
III. SELECTION OF ORIGINAL SITES AND DRAWINGS
We describe an experiment here in which 18 people with various levels of experience were all
asked to record the same panels. We then digitize photographs of the panels and we digitize the
drawings. After applying an image registration technique to the photos and drawings, the images
are compared quantitatively.
The panels selected here in this first stage of the study were selected primarily for convenience.
While we would normally select a more distinctly defined set of glyphs for a study like this, in
this case these were the glyphs available when the 18 people were ready to do the drawing.
These drawings were records of panels at an Aboriginal site on Mt. Mulligan in Queensland,
Australia. The panels represent a wide range of distinguishability. They represent figures that are
not easily recognizable and they are in a position in a rock shelter that is relatively inaccessible.
Photographs of each panel were taken to the best of our ability. These photos were not as good as
we would have liked, but they were the best that could be obtained, given the relative
inaccessibility of the panels in the rock shelter. They represent one of the more difficult photo
situations and present a nice opportunity to demonstrate how geometric mapping can improve
photographic records even in situations where good photographs are not possible.
V. DRAWINGS AND DRAWERS
The drawings for this experiment were made by 18 members of an Earthwatch team on a field
expedition during the summer of 1997. The members ranged in experience from professional
archeologists with extensive experience with rock art from this region to artists with little rock
art experience to complete novices.
VI. DIGITIZATION AND SELECTION OF CONTROL POINTS
The photographs and freehand drawings from the study were digitized on a flatbed scanner. The
photographic images were stored in the computer in JPEG format and the drawings were stored
in GIF format. Both types of images were displayed using an image processing program (Adobe
Photoshop) so that digital tracings of the photos and drawings could be developed and the pixel
coordinates of key "control points" in the images could be recorded. Figure 1 shows a split
screen in Photoshop of an original photograph and its tracing (the original photo on top and the
tracing on the bottom).
Figure 1: Adobe Photoshop Split Screen of Origianl Photo (on top) and Tracing (on bottom)
The next step is to get ready for registration of the images. To do this, we need to select control
points for the images. A control point is an easily identified reference mark of some kind in the
figure or glyph that can be used as a basis for image registration. These are the points we are
going to try to make match during the registration process. We wish to find these marks in all of
the drawings and photographs and they should be spread out over the images to make sure all
parts of the images register properly. The registration process will ensure that these control
points match geometrically as closely as possible. If the control points match, the rest of the
images should match also. Any failures to match will be due to the fact that the images are not
geometrically conformable. Figure 2 shows one of the images of a drawing with the 8 control
points identified by squares with the diagonals connected.
Figure 2: Original Image Showing Control Points As Squares with Diagonals Connected (8
VII. CALCULATING THE IMAGE MAPPING COEFFICIENTS
As an image is registered, each point at position (x,y) in the original image is mapped to a new
position (x',y') in the new registered image according to the mapping:
x' = a*x + b*y + c + Ex
y' = d*x + e*y + f + Ey
The coefficients, a, b, c, d, e, and f, define the mapping from the old image (x,y) to the new
image (x',y'). These coefficients are derived by using the control points to do a least squares
solution for the coefficients. The Ex and Ey factors represent the errors in the mapping and these
can be used as a quantitative measure of the quality and consistency of the geometry of the
recordings. So from the control points we can derive the mean squared values of these errors.
VIII. CALCULATING THE NEW REGISTERED IMAGE
If the images were all exact geometric copies of the same figure and if the figure were planar, all
of the drawings and photos would be mapped by a planar mapping onto a consistent geometric
plane. That is, under the above assumptions, we should be able to register the images exactly.
The registration would correct for any translation, orientation and scale differences in the
original image. Here, because we know the drawings are not exact copies, we expect differences
even after registration. But by doing the registration we are eliminating the translation,
orientation and scale differences (which are unimportant) and only have warping and drawing
error differences left. Figure 3 shows a reference image (left) and another image before (center)
and after (right) it has been mapped to match the geometry of the reference image. Notice that
before registration the second image (center) appears smaller than the reference (left) and the
bars along the tops seem at different angles. The effect of the registration on the second image
(right) is to expand its width and rotate it slightly counterclockwise. A careful check of the
control points in the left and right images will show they match reasonably well.
Figure 3: Composite Image Showing Reference Image, A Second Image Original and the
Second Image Registered
Finally, once the images have been mapped onto a consistent geometry, we can measure
quantitatively the agreement between the 2 drawings. Again, we want quantitative measures
because we want to compare different recording methods.
The first measure we can use is the average error which was derived from the least squares
solution for the coefficients for the control points. For the images above, the average error in
matching a control point was about 8% of the width of the figure. This is very large and shows
the basic lack of geometric correspondence between the 2 drawings.
The second measure we can use to compare the drawings is the percentage of the areas of the
features of the image that overlap. These percentages represent the agreement in the content of
the drawings and can be used as another quantitative measure of the recording quality. Figure 4
shows the overlapped images including the areas that are equal and the areas that differ. In this
figure, areas that are black and areas that are white are areas that agree. Red and cyan areas are
areas that differ. Again we can see there is significant disagreement between the 2 drawings.
Figure 4: A Composite Image Showing the Overlaps of the Drawings
The degree of mismatch shown here is not typical of the 18 drawings that were made. In fact
most of the others were far worse! We can only conclude that freehand drawing is a very
inaccurate way to record rock art. This iconclusion, of course, comes as no surprise.
In addition to normal drawing, with modern digital equipment in the field, it is possible to use
digital photographic guided drawing. This concept begins with a digital photograph taken by a
digital camera. This photograph is then transferred to a printer, either directly or by way of a
laptop computer. The image is then printed lightly (i.e. very low contrast) on paper. This printout
can be accomplished in the field with a digital camera, a portable printer and possibly a laptop
computer. The recorder can then return to the rock art and compare the printed image to the
original glyph, making sketches of added areas or deleted areas in addition to other notations.
Both the original image and the corrected drawing can be retained in the database for comparison
This kind of drawing is a new technique and we cannot predict how useful it will be until we
have field-tested it. But it is likely that this method will be very useful and accurate. Drawings
produced in this way simply cannot be as inaccurate as those shown above. And the drawer gets
to spend more time concentrating on image details without worrying about geometry.
We hope to use some of the methods and quantitative measures developed here to study the
effects on drawing accuracy of factors such as
1. Simple vs. Complex glyphs
2. Faint vs. Distinct glyphs
3. The Effect of View Angle
4. Recognizable vs. Unrecognizable figures
5. Amateur vs. Professional Drawers
1. Castleman, Kenneth R., Digital Image Processing, Prentice-Hall, 1996, pp 115-141.
2. Sternberg, P. R., and Brayer, J. M., "Composite Imaging: A New Technique in
Bibliographic Research," Papers of the Bibliographical Society of America, vol. 77,