Tracking of tubular molecules for scientific applications
Parvin, B.A.
Peng, C.
Johnston, W.
Maestre, P.M.
Div. of Comput. Sci. & Eng., Lawrence Berkeley Nat.Lab., CA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Aug 1995
Volume: 17,
Issue: 8
On page(s): 800-805
ISSN: 0162-8828
References Cited: 17
CODEN: ITPIDJ
INSPEC Accession Number: 5024400
Digital Object Identifier: 10.1109/34.400570
Current Version Published: 2002-08-06
Abstract
In this paper, we present a system for detection and tracking of
tubular molecules in images. The automatic detection and
characterization of the shape, location, and motion of these molecules
can enable new laboratory protocols in several scientific disciplines.
The uniqueness of the proposed system is twofold: At the macro level,
the novelty of the system lies in the integration of object localization
and tracking using geometric properties; at the micro level, in the use
of high and low level constraints to model the detection and tracking
subsystem. The underlying philosophy for object detection is to extract
perceptually significant features from the pixel level image, and then
use these high level cues to refine the precise boundaries. In the case
of tubular molecules, the perceptually significant features are
antiparallel line segments or, equivalently, their axis of symmetries.
The axis of symmetry infers a coarse description of the object in terms
of a bounding polygon. The polygon then provides the necessary boundary
condition for the refinement process, which is based on dynamic
programming. For tracking the object in a time sequence of images, the
refined contour is then projected onto each consecutive frame
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