Transcript No Slide Title

Feature Detection and Outline Registration in Dorsal Fin Images
A. S. Russell, K. R. Debure, Eckerd College, St. Petersburg, FL
Abstract
Outline Registration
Marine mammologists studying the behavior and ecology of wild dolphins often
employ photo-identification as a means of associating observational data with
individual dolphins. DARWIN is a computer program that addresses the difficulties of
manual photo-identification by applying computer vision and signal processing
techniques to automate much of the process. The DARWIN system allows a
researcher to query a database of previously identified dolphin dorsal fin images
with an image of an unidentified dolphin's fin. The researcher may then browse a
rank ordered list of database fin images that most closely resemble the query image
to identify the dorsal fin. Since the examination begins with fins most similar to the
unidentified fin, the time required of the researcher to identify the correct match is
potentially reduced. A major challenge in the automated process arises from the
presence of perspective distortions, which can cause different views of the same
dorsal fin to differ significantly in appearance, making direct comparison extremely
problematic. Current research has focused on methods of distortion correction to
quickly transform images so that it appears fins were photographed from the same
angle. Locating salient fin feature points provides a basis for this transformation by
allowing a direct determination of any rotational, translational, and scaling factors
necessary to compensate for perspective distortions. Preliminary results show that
this approach produces appropriate transformations when the feature points are
accurately identified. The resulting distortion correction produces a marked
improvement in the similarity of the dorsal fin outlines. This new approach promises
improved accuracy and a compelling alternative to manual photo-identification.
Ideally, we would like to transform the outlines so that it appears the original fins
were photographed from the same angle. The transformation process is as
follows:
• locate sets of common feature points on pairs of fin outlines
• compute transformation matrix which maps one set of points onto the other
• apply transformation to entire outline
Figure 3: Left: Dorsal fin image with characteristic feature points indicated in red. Center: Extracted
outline with feature points marked. Right: Chain code of angles comprising fin outline.
Direct comparison of chain code representations is problematic since perspective
distortions can cause outlines extracted from multiple photographs of the same
dolphin’s dorsal fin to differ significantly. We present a technique to transform the
outlines so that it appears the original fins were photographed from the same
angle. Locating common feature points on fin outlines provides a basis for this
transformation.
world results of the
registration process.
In each set, the
originally extracted
outlines are pictured
on the top. The
automatically
registered outlines
are pictured on the
bottom.
Automatic Feature Selection
Starting Point of the Leading Edge
• compute absolute angles between successive points along the edge
Introduction
DARWIN is a computer program which aids marine mammalogists in the
identification of dolphins and in the management of a database of observational
information. DARWIN graphically presents the digitized dorsal fin images and
associated textual sighting information.
• identify threshold angle which maximizes between class variance [3] of the
angles which comprise the proper leading edge of the fin and the angles
which are associated with the body of the dolphin.
The database of information can be:
• discard line segments at leftmost end of outline if their angles diverge
significantly from predominant edge orientation
•
queried for images which are
similar to the dorsal fin image of
an unknown individual
• select the initial point of the leading edge if no such divergence exists
•
queried with the name of a
specific individual
•
organized and viewed by
particular sighting information
such as location, date, or fin
damage category
Tip of the Dorsal Fin
• compute a wavelet decomposition
of the chain of angles comprising
the fin outline
Figure 1: Following a query of the dorsal fin database,
DARWIN presents icons representing fin images which
most closely resemble the unknown fin image.
Dorsal Fin Identification
In order to query the database for fins resembling the unknown dolphin:
1. The user traces a rough outline of the dorsal fin.
2. Active contours [1] are employed
to accurately position the points
comprising the outline onto the
actual edge of the fin. The fin
outline is extracted as a series of
two-dimensional x and y
coordinates.
• identify largest positive local
maximum in a coarse level
representation of the outline
(roughly indicates the position of
the fin tip)
• track position back through the
finer scale representations to more
accurately identify the position.
Figure 4: Finding the tip from the wavelet transform.
The original chain code is on top, with increasingly
coarse details following. The position of the tip is
found on the coarsest (bottom) level, and tracked to
the finer levels. The tracking of the tip is marked at
each level.
• identify candidate notches as local minima with large magnitudes at an
intermediate transform level
sketch based query of the database of dorsal fins. This
window is also used to add new dorsal fin images and
associated sighting data to the database.
Preliminary results suggest that the registration method presented herein shows
significant promise in perspective correction of dolphin dorsal fin images. The
effectiveness of the method is, of course, entirely dependent upon the accuracy of
extracted features. Fortunately, features are well extracted in many cases: The
identification of the fin tip is quite stable even when part of the tip is absent. Notch
identification is reasonably successful even in outlines where multiple notches are
present or the most prominent notch is relatively small. The starting point of the
leading edge presents more difficulty when the area where the dorsal fin meets the
dolphin’s body is not contained in the outline. A possible solution for this fault is to
detect when an outline may lack part of the fin's leading edge, and alternatively use
a different feature point, such as the end of the leading edge.
References
• analyze wavelet decomposition of angles comprising the dorsal fin outline,
localizing search to the trailing edge of the dorsal fin
Figure 2: The tracing window allows the user to perform a
Conclusion
In any case, the process has the ability to improve the registration of outlines
considerably. The improved registration suitably corrects for perspective distortion
and makes fin outline comparison and subsequent retrieval of appropriate images
far less problematic.
Most Prominent Notch
3. The extracted outline is reduced
to a one-dimensional series of
angular changes between points
called a chain code.
4. The chain-coded outline is
compared against fin outlines in
the database.
Figure 5: Two real-
• track candidate notches to coarser level. Identify most prominent notch as the
minimum that decreases most slowly in magnitude
[1] M. Kass, A. Witkin, and D. Terzopoulos. Snakes: Active contour models.
International Journal of Computer Vision, pages 259--268, 1987.
[2] S.Mallat. Characterization of signals from multiscale edges. IEEE Trans. on Pattern
Analysis and Machine Intelligence, 14(7):710--732, July 1992.
[3] N. Otsu. A threshold selection method from gray level histograms. IEEE Trans. on
Systems, Man, and Cybernetics, SMC-9:62--66, January 1992.
Acknowledgements
The authors would like to thank the the following organizations for support of this
research:
•
National Science Foundation
•
National Marine Fisheries Services
•
Eckerd College
• back-track to the finest level of detail to accurately identify position of notch
Dorsal fin images courtesy of Eckerd College Dolphin Project.