Issue No. 08 - August (1995 vol. 17)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.400570
<p><it>Abstract</it>—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.</p>
F. Maestre, B. Parvin, C. Peng and W. Johnston, "Tracking of Tubular Molecules for Scientific Applications," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 17, no. , pp. 800-805, 1995.