TRACCE no. 11 – by Phil Clogg, Margarita Díaz-Andreu
Digital Image Processing and the Recording of Rock Art.
Traditional techniques of recording entail a high degree of subjectivity due to the important number of decisions that the specialist has to take. Different recordings on the same motif usually show contradictory interpretations of certain features…
Traditional techniques of recording entail a high degree of subjectivity due to the important number of decisions that the specialist has to take. Different recordings on the same motif usually show contradictory interpretations of certain features. This is not a case specific to any country or to a particular period of rock art recording. This is the reason for bringing into the field of rock art recording new techniques which can reduce subjectivity to a great extent. Photography and DIP combined seem to offer great advances in this area.
In this article, we have applied the use of DIP techniques to a case study, on one of the figures of the Selva Pascuala site in Villar del Humo (Spain).
The three previous recordings of this motif were contradictory, showing the problems of traditional techniques. The system available in the Department of Archaeology of the University of Durham (PC_Image Plus by Foster Findlay Associates) only allowed us to conduct this research using medium resolution grey scale images, and whilst this placed obvious restrictions on the quality of the output it has provided a firm base from which to assess the nature and value of digital image processing techniques within the study of rock art.
Our overall aims are to investigate and enhance poorly defined areas within the image and extract all information pertaining to the motifs in a form which can best present our interpretation of the rock art. Two major stages can be defined in the application of digital image processing: the pre-processing and the processing.
In an ideal world pre-processing the image should not be necessary. In the real world, however, images have a series of problems that have to be dealt with in order to allow the processing of the image. In our case, both the colour of the rock and that of the paintings are red, and this coincidence obviously affects the ease with which the features can be discriminated. In terms of the surface, despite it being roughly flat, the granulate structure of sandstone and its layered composition influence the reading of the image. Moreover, there are a few places in which the surface is irregular, because of a breach and also because of a few hollows, which in our case mainly affects the area around one of the rear legs of the bull, a problem which also affected previous recordings.
The first approach followed was working with the image as it stands. We begin by processing the whole image. Our aim at this stage was to highlight the information which was not obviously visible. In the first place, problems of variation in lighting and shadows may be overcome to a certain extent by the use of a variation of the Wallis algorithm. A number of standard techniques can then be applied in sequence, the main ones being contrast enhancement, edge enhancement, and image sharpening. Furthermore, the use of the random colour look-up tables is a procedure which is not time consuming but can easily serve to emphasise features that may warrant further investigation. This facilitates the identification of details and also can present the image in an unconventional manner thus challenging our pre-conceived ideas of what we are seeing.
The second approach was to try to remove the background interference, i.e. texture of the rock itself. One line of enquiry would be through the processing of the image using multiple image operations: superimposition of two or more images either through image subtraction or addition of a further image.
Another method of extracting information from the whole image is using the technique of edge detection. Filters can be applied which enhance these boundaries by providing outlines of features within the image. The most effective of these is the sobel filter which picks up edges in all directions. The sobel filter produces an outline of the image. To facilitate interpretation it is often necessary to superimpose the sobel image onto the real image in order to the highlight the relationship between the two. Once this has been accomplished a threshold function can then be applied to the sobel image thus producing a binary image superimposed upon the original (a binar image is one which is composed of only two colours thus giving a high definition to any motif). By using a technique termed Skeletonise in the PC_image programme the lines within the binary can be reduced to a width of one pixel thus providing a high level of detail. The image can then be filtered automatically to remove any information below a pre-defined size producing a detailed outline of the major features. At this point we found that there are always a number of discontinuities within the outline and that some of the less well defined detail is missing (for example the tail). To complete the image at this stage would require a good deal of manual editing, something which we feel should be avoided, and so whilst this sequence shows some potential we consider that further development is necessary for its full realisation.
The next stage in pre-process is to check problematic areas by zooming up the image to enlarge the area. We can then apply a threshold filter to select the problematic areas and convert them into binary images. This separates the painted area from the background. Building up the image from 2 or 3 threshold operations will usually leave us with a good approximation of the motif. If we then reduce this to an outline form we are able to superimpose this binary image over a variety of our pre-processed images in order to adjust the fine details of the shape.
All these pre-processing stages provides us with an image ready for study and interpretation. We initially considered that in our approach the ideal result of the pre-processing would produce an image to which we could apply a threshold function to convert or separate out the actual painted area from the background. In practice this use of a single process did not appear to be possible. However, the combination of multiple threshold processes using different values or from different pre-processed images can be used to easily and quickly build up the complete image. This also provides us with the opportunity of using different representations such as colour or shading for describing vague or unclear motifs. We are also aware that a combination of the described thresholding technique and the edge detection sequence may provide a highly detailed and objective final recording and this is one area that we intend to pursue in the future.
The result obtained confirms that the use of image processing can only add to the knowledge and interpretation of rock art, particularly as we have been able to check previously problematic areas with a detail not available with the more traditional techniques. In the future we would like to move further in the recording of both pictographs and petroglyphs by applying this knowledge to the process of high resolution, full colour images which will allow much greater understanding in interpretation particularly for specific problems such as repaintings, different densities of painting and use of different colours or tones of colours.
Department of Archaeology
University of Durham
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