  (abridged) We describe an image-comparison technique of Heidemann and Ritter
that uses image compression, and is capable of: (i) detecting novel textures in
a series of images, as well as of: (ii) alerting the user to the similarity of
a new image to a previously-observed texture. This image-comparison technique
has been implemented and tested using our Astrobiology Phone-cam system, which
employs Bluetooth communication to send images to a local laptop server in the
field for the image-compression analysis. We tested the system in a field site
displaying a heterogeneous suite of sandstones, limestones, mudstones and
coalbeds. Some of the rocks are partly covered with lichen. The image-matching
procedure of this system performed very well with data obtained through our
field test, grouping all images of yellow lichens together and grouping all
images of a coal bed together, and giving a 91% accuracy for similarity
detection. Such similarity detection could be employed to make maps of
different geological units. The novelty-detection performance of our system was
also rather good (a 64% accuracy). Such novelty detection may become valuable
in searching for new geological units, which could be of astrobiological
interest. The image-comparison technique is an unsupervised technique that is
not capable of directly classifying an image as containing a particular
geological feature; labeling of such geological features is done post facto by
human geologists associated with this study, for the purpose of analyzing the
system's performance. By providing more advanced capabilities for similarity
detection and novelty detection, this image-compression technique could be
useful in giving more scientific autonomy to robotic planetary rovers, and in
assisting human astronauts in their geological exploration and assessment.
